Flowspace: CoWorking Spaces in London | Book a Meeting Room - Workspace Booking for Hybrid Teams | On-Demand Access, Quick Office Search, All-in-One Platform

Workspace booking platform | Coworking spaces in London & the UK

Flowspace | 6,671 followers on LinkedIn. Powering independent ecommerce fulfillment | Flowspace is an ecommerce fulfillment platform helping brands meet their customers’ post-purchase expectations in the real world. The company’s cloud-based software, integrated within a network of +150 ...

Flowspace | LinkedIn

Pay-as-you-go access the best coworking spaces, fitness studios, and health spas around you.

Flow | Walk-Ins Welcome

Flowspace provides a reliable and scalable fulfillment and distribution service in a single, cloud-based platform with on-demand warehousing. Join us!

Careers at Flowspace - Join us as we Redefine Commerce

See what employees say it&#x27;s like to work at Flowspace. Salaries, reviews, and more - all posted by employees working at Flowspace.

Working at Flowspace | Glassdoor

Flow Workspaces bestow a progressive and growth-oriented atmosphere with freedom and creativity to do your work with all the needful resources. We envision to provide a complete ecosystem with the provision of meeting rooms, fully equipped workstations and lounge put together in a single setting ...

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Sales Enquiries 1-206-859-6999 · Announcement: FlowWorks has rebranded as infinitii ai. Click here to visit our new corporate website and read more about our next generation of Machine Learning products

FlowWorks – Know your data

Workflows are the activities needed to complete a task. Find out about the various types of workflows and how they&#x27;re created, used, managed and automated.

What is a Workflow? Definition and Examples

Find out what works well at Flow Space from the people who know best. Get the inside scoop on jobs, salaries, top office locations, and CEO insights. Compare pay for popular roles and read about the team’s work-life balance. Uncover why Flow Space is the best company for you.

Flow Space Careers and Employment | Indeed.com

Flowspace was created by industry veterans to provide an easy to use, cloud-based logistics platform for businesses of all sizes to scale their operations.

Flowspace: Learn About Us and Our Founders

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FLOWhab - Coworking space in Nis, Serbia

In the post-war era, the work of W. Edwards Deming and Joseph M. Juran led to a focus on quality, first in Japanese companies, and more globally from the 1980s: there were various movements ranging from total quality management to Six Sigma, and then more qualitative notions of business process ...

Workflow - Wikipedia

WOLF is a co-working space that believe in finding the seed in you and helping to make it grow through the friendly community.

WOLF Co-Working Space

WeWork’s founder is back with a billion-dollar venture.

WeWork’s Adam Neumann Gets Backing from Andreesen Horowitz - ...

Ensure that important processes are completed the right way, every time. In this article, we will explain why your business needs efficient workflows and show you some workflow examples to help you get started.

What Is a Workflow? Benefits and Examples | Lucidchart Blog

Learn how you can adopt the Space Git flow to achieve better code quality and produce more stable builds.

Introducing the Space Git Flow | The Space Blog

Flowspace jobs

Workflow management software helps you manage and automate your business processes. Check out the best tools to automate your workflow.

21 Best Workflow Management Software of 2024

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Flow Workspaces

For developers, achieving a flow state is essential for optimal productivity and focus during coding. However, traditional developer workflows often hinder the ability to reach this state due to constant context switching and operational tasks. DevEx recognizes the importance of promoting a as a fundamental developer experience aspect. flow state We will explore key principles for designing workspaces that facilitate flow state for developers. We will also demonstrate how the platforms integrate these principles into the developer experience to enhance productivity. Standardized Development Environment (SDE) Principles for Designing Flow State-Enabled Workspaces To promote a flow state in developer workspaces, consider the following principles: 1. Minimize Distractions Reduce or eliminate sources of distraction, such as notifications, multitasking, and operational tasks. 2. Foster Immersed Focus Design interactions that minimize interruptions and make it easy for developers to concentrate by tuning out distractions. 3. Streamline Setup Enable developers to start coding within minutes by automating environment setup. 4. Simplify Access Provide straightforward access to approved tools with consistent and reliable configurations. Let's explore how the Standardized Development Environment (SDE) optimizes the developer experience to facilitate the flow state. How SDE Enhances Flow State in Workspaces SDE offers dedicated, immutable workspaces that empower developers to immerse themselves in a flow state. By automating operational tasks and providing structured access, SDE removes distractions. isolate developers from context switching and interruptions through permissions and controls. Workspaces Templated environments ensure quick and consistent setup, allowing developers to commence coding rapidly. All necessary tools are preconfigured and readily accessible with a single click. Collaboration occurs seamlessly within the flow state through immersive capabilities like co-editing, terminal sharing, and live changes. This eliminates distractions caused by tool switching and meetings. SDE leverages DevEx principles to create an optimized developer experience that enables a sustained flow state, fostering deep focus and productivity. Key Features that Support and Enhance Flow State SDE incorporates specific features designed to minimize disruptions and maintain developers' focus within the flow state: : Each project or task receives a fresh and separate environment for developers. Dedicated Environments : Granular permissions eliminate external distractions and interruptions. Isolation Controls : Consistent templated setup enables developers to start coding in minutes. Automated Provisioning : Essential tools are built-in and easily accessible through single sign-on. Integrated Tools : Co-editing, streaming changes, and terminal sharing facilitate collaboration within the flow state. Immersive Collaboration : Seamless handling of tests, builds, and deployments without interrupting the flow. Background Automation By incorporating these capabilities, SDE creates an ideal environment for a sustained flow state, enabling continuous productivity. The Productivity Impact of Flow State Promoting flow state through workspace design has a significant impact on productivity: : Minimizing context switching leads to increased output. 2-5 times greater productivity : Fewer task switches and interruptions result in lower fatigue levels. Reduced fatigue : Focusing on challenging and meaningful work increases engagement. Enhanced engagement : Peak cognitive performance allows for the execution of higher caliber work. Higher quality output : By sustaining focus and fostering creativity, innovation flourishes. Increased innovation The evidence is clear: when developer workspaces are designed to promote flow state, productivity, innovation velocity, and developer satisfaction experience exponential gains. Examples of Standardized Development Environments (SDEs) Several SDE platforms have emerged to address the need for optimized developer workspaces. Let's explore a few notable examples: delivers an SDE that allows developers to have instant, cloud-based, and fully automated development environments. By integrating with popular version control systems like GitHub, GitLab, and Bitbucket, Gitpod provides developers with pre-configured environments that smoothly align with their project repositories. Gitpod offers an SDE that focuses on providing consistent and shareable development environments. With Coder, developers can effortlessly spin up self-contained, reproducible workspaces using Docker containers. This flexibility enables teams to collaborate seamlessly, sharing the same coding environment for improved synchronization and productivity. Coder creates on-demand, isolated, and reproducible environments using Kubernetes and containerization technologies. With Devpod's SDE approach, developers can quickly provision fully configured development environments that mirror the production environment while minimizing setup time and ensuring team consistency. Devpod provides an SDE solution that accelerates the development workflow by offering interactive, cloud-based coding environments. Through Devzero, developers can access a curated set of standardized tools and libraries, all easily accessible in a single environment. This ensures a seamless development experience without the burden of local environment setup. Devzero is an SDE platform built on the experience of Codeanywhere that emphasizes the promotion of flow state by automating operational tasks and streamlining access to tools. With dedicated, immutable workspaces, Daytona isolates developers from distractions and interruptions. Daytona enables seamless coding experiences that amplify productivity and creativity by incorporating templated environments and immersive collaboration capabilities. Daytona By leveraging these standardized environments, developers can achieve a flow state more easily, leading to increased productivity, improved collaboration, and enhanced developer satisfaction. Optimization for Flow State Flow state acts as a catalyst, supercharging developer productivity. Optimize your workspaces by eliminating distractions and streamlining access to tools and environments to harness its power. Take inspiration from the Standardized Development Environment (SDE) and its developer experience-focused workspace design. Identify manual tasks and context-switching workflows that disrupt developer focus and implement automation and policy solutions to address them. By prioritizing flow state through workspace design, you will , accelerate innovation, and cultivate a creative mindset throughout your engineering organization. Immerse your developers in their craft, and be prepared for remarkable achievements. enhance productivity

The Power of Achieving Flow State in DevEx

In our last two articles, we explored how to configure CI/CD for Heroku using Heroku pipelines. When viewing a pipeline within the Heroku dashboard, you can easily start a deployment or promote your code from one environment to the next with the click of a button. From the dashboard, you can monitor the deployment and view its progress. This all works really well, assuming that you have Heroku open in your browser. But, what if you wanted to do it all from Slack? Software engineers use a lot of apps at work. Throughout the day, we are constantly bouncing between Zoom meetings, Jira tasks, Slack conversations, GitHub, email, our calendar, and our IDE. This context switching can be exhausting and also lead to a lot of visual clutter on our monitors. Sometimes, it’s nice to just live in Slack, and that’s why many tools offer Slack integrations. With these Slack integrations, you can monitor various processes and even use shortcut commands to trigger actions. Heroku ChatOps, the Heroku Slack integration, allows you to start and monitor deployments directly from Slack. In this article, we’ll explore some of the Slack commands it offers. Getting Started If you’d like to follow along throughout this tutorial, you’ll need a Heroku account and a GitHub account. You can create a Heroku account here, and you can create a GitHub account here. The demo app that we will use with our Heroku pipeline in this article is deployed to Heroku, and the code is hosted on GitHub. Create Our Heroku Pipeline We won’t go through the step-by-step process of creating a Heroku pipeline in this article. Refer to these articles for a walkthrough of creating a Heroku pipeline: How to create a Heroku pipeline with a staging and production app and a single main branch
How to create a Heroku pipeline with a staging and production app with a dev branch and a main branch You can also read the Heroku docs for Heroku pipelines. Configuring your Heroku pipeline includes the following steps: Create a GitHub repo.
Create a Heroku pipeline.
Connect the GitHub repo to the Heroku pipeline.
Add a staging app to the pipeline.
Add a production app to the pipeline. The other activities that you’ll see in those articles, such as configuring review apps, Heroku CI, or automated deployments are optional. In fact, for the purposes of this demo, I recommend not configuring automated deployments, since we’ll be using some Slack commands to start the deployments. When you’re done, you should have a Heroku pipeline that looks something like this: Connect to Slack Now that you have your Heroku pipeline created, it’s time for the fun part: integrating with Slack. You can install the Heroku ChatOps Slack app here. Clicking that link will prompt you to grant the Heroku ChatOps app permission to access your Slack workspace: After that, you can add the Heroku ChatOps app to any Slack channel in your workspace. After adding the app, type /h login and hit Enter. This will prompt you to connect your Heroku and GitHub accounts. You’ll see several Heroku OAuth and GitHub OAuth screens where you confirm connecting these accounts. (As a personal anecdote, I found that it took me several tries to connect my Heroku account and my GitHub account. It may be due to having several Slack workspaces to choose from, but I’m not sure.) After connecting your Heroku account and your GitHub account, you’re ready to start using Heroku in Slack. View All Pipelines To view all deployable pipelines, you can type /h pipelines: View Pipeline Info To see information about any given pipeline, type /h info <PIPELINE_NAME>. (Anything you see in angle brackets throughout this article should be replaced by an actual value. In this case, the value would be the name of a pipeline — for example, “heroku-flow-demo-pipeline”.) View Past Releases To view a history of past releases for any given pipeline, type /h releases <PIPELINE_NAME>. This command defaults to showing you past releases for the production app, so if you want to see the past releases for the staging app, you can type /h releases <PIPELINE_NAME> in <STAGE_NAME>, where <STAGE_NAME> is “staging.” Deploy to Staging Now that we know which pipelines are available, we can see information about any given pipeline along with when the code was last released for that pipeline. We’re ready to trigger a deployment. Most engineering organizations have a Slack channel (or channels) where they monitor deployments. Imagine being able to start a deployment right from that channel and monitor it as it goes out! That’s exactly what we’ll do next. To start a deployment to your staging environment, type /h deploy <PIPELINE_NAME> to <STAGE_NAME>, where <STAGE_NAME> is “staging.” After running that command, an initial message is posted to communicate that the app is being deployed. Shortly after, you’ll also see several more messages; this time, in a Slack thread on the original message: If you want to verify what you’re seeing in Slack, you can always check the Heroku pipeline in your Heroku dashboard. You’ll see the same information: The staging app has been deployed! Promote to Production Now, let’s promote our app to production. Without the Slack commands, we could navigate to our Heroku pipeline, click the “Promote to production” button, and then confirm that action in the modal dialog that appears. However, we’d prefer to stay in Slack. To promote the app to production from Slack, type /h promote <PIPELINE_NAME>. Just like with the staging deployment, an initial Slack message will be sent, followed by several other messages as the production deployment goes out: And — voilà — the latest changes to the app are now in production! Conclusion Now, you can start and monitor Heroku app deployments all from Slack — no need to context switch or move between multiple apps. For more use cases and advanced setups, you can also check out the docs. Happy deploying! In our last two articles, we explored how to configure CI/CD for Heroku using Heroku pipelines . When viewing a pipeline within the Heroku dashboard, you can easily start a deployment or promote your code from one environment to the next with the click of a button. From the dashboard, you can monitor the deployment and view its progress. configure CI/CD for Heroku using Heroku pipelines start a deployment or promote your code from one environment to the next This all works really well, assuming that you have Heroku open in your browser. But, what if you wanted to do it all from Slack? Software engineers use a lot of apps at work. Throughout the day, we are constantly bouncing between Zoom meetings, Jira tasks, Slack conversations, GitHub, email, our calendar, and our IDE. This context switching can be exhausting and also lead to a lot of visual clutter on our monitors. Sometimes, it’s nice to just live in Slack, and that’s why many tools offer Slack integrations. With these Slack integrations, you can monitor various processes and even use shortcut commands to trigger actions. Heroku ChatOps , the Heroku Slack integration, allows you to start and monitor deployments directly from Slack. In this article, we’ll explore some of the Slack commands it offers. Heroku ChatOps Getting Started If you’d like to follow along throughout this tutorial, you’ll need a Heroku account and a GitHub account. You can create a Heroku account here , and you can create a GitHub account here . create a Heroku account here create a GitHub account here The demo app that we will use with our Heroku pipeline in this article is deployed to Heroku, and the code is hosted on GitHub . the code is hosted on GitHub Create Our Heroku Pipeline We won’t go through the step-by-step process of creating a Heroku pipeline in this article. Refer to these articles for a walkthrough of creating a Heroku pipeline: How to create a Heroku pipeline with a staging and production app and a single main branch How to create a Heroku pipeline with a staging and production app with a dev branch and a main branch How to create a Heroku pipeline with a staging and production app and a single main branch How to create a Heroku pipeline with a staging and production app and a single main branch How to create a Heroku pipeline with a staging and production app with a dev branch and a main branch How to create a Heroku pipeline with a staging and production app with a dev branch and a main branch You can also read the Heroku docs for Heroku pipelines . Heroku docs for Heroku pipelines Configuring your Heroku pipeline includes the following steps: Create a GitHub repo. Create a Heroku pipeline. Connect the GitHub repo to the Heroku pipeline. Add a staging app to the pipeline. Add a production app to the pipeline. Create a GitHub repo. Create a Heroku pipeline. Connect the GitHub repo to the Heroku pipeline. Add a staging app to the pipeline. Add a production app to the pipeline. The other activities that you’ll see in those articles, such as configuring review apps, Heroku CI, or automated deployments are optional. In fact, for the purposes of this demo, I recommend not configuring automated deployments, since we’ll be using some Slack commands to start the deployments. not When you’re done, you should have a Heroku pipeline that looks something like this: Connect to Slack Now that you have your Heroku pipeline created, it’s time for the fun part: integrating with Slack. You can install the Heroku ChatOps Slack app here . install the Heroku ChatOps Slack app here Clicking that link will prompt you to grant the Heroku ChatOps app permission to access your Slack workspace: After that, you can add the Heroku ChatOps app to any Slack channel in your workspace. After adding the app, type /h login and hit Enter. This will prompt you to connect your Heroku and GitHub accounts. You’ll see several Heroku OAuth and GitHub OAuth screens where you confirm connecting these accounts. /h login (As a personal anecdote, I found that it took me several tries to connect my Heroku account and my GitHub account. It may be due to having several Slack workspaces to choose from, but I’m not sure.) (As a personal anecdote, I found that it took me several tries to connect my Heroku account and my GitHub account. It may be due to having several Slack workspaces to choose from, but I’m not sure.) After connecting your Heroku account and your GitHub account, you’re ready to start using Heroku in Slack. View All Pipelines To view all deployable pipelines, you can type /h pipelines : /h pipelines View Pipeline Info To see information about any given pipeline, type /h info <PIPELINE_NAME> . (Anything you see in angle brackets throughout this article should be replaced by an actual value. In this case, the value would be the name of a pipeline — for example, “heroku-flow-demo-pipeline”.) /h info <PIPELINE_NAME> View Past Releases To view a history of past releases for any given pipeline, type /h releases <PIPELINE_NAME> . /h releases <PIPELINE_NAME> This command defaults to showing you past releases for the production app, so if you want to see the past releases for the staging app, you can type /h releases <PIPELINE_NAME> in <STAGE_NAME> , where <STAGE_NAME> is “staging.” /h releases <PIPELINE_NAME> in <STAGE_NAME> <STAGE_NAME> Deploy to Staging Now that we know which pipelines are available, we can see information about any given pipeline along with when the code was last released for that pipeline. We’re ready to trigger a deployment. Most engineering organizations have a Slack channel (or channels) where they monitor deployments. Imagine being able to start a deployment right from that channel and monitor it as it goes out! That’s exactly what we’ll do next. To start a deployment to your staging environment, type /h deploy <PIPELINE_NAME> to <STAGE_NAME> , where <STAGE_NAME> is “staging.” /h deploy <PIPELINE_NAME> to <STAGE_NAME> <STAGE_NAME> After running that command, an initial message is posted to communicate that the app is being deployed. Shortly after, you’ll also see several more messages; this time, in a Slack thread on the original message: If you want to verify what you’re seeing in Slack, you can always check the Heroku pipeline in your Heroku dashboard. You’ll see the same information: The staging app has been deployed! Promote to Production Now, let’s promote our app to production. Without the Slack commands, we could navigate to our Heroku pipeline, click the “Promote to production” button, and then confirm that action in the modal dialog that appears. However, we’d prefer to stay in Slack. could To promote the app to production from Slack, type /h promote <PIPELINE_NAME> . /h promote <PIPELINE_NAME> Just like with the staging deployment, an initial Slack message will be sent, followed by several other messages as the production deployment goes out: And — voilà — the latest changes to the app are now in production! Conclusion Now, you can start and monitor Heroku app deployments all from Slack — no need to context switch or move between multiple apps. For more use cases and advanced setups, you can also check out the docs . check out the docs Happy deploying!

Heroku for ChatOps: How to Start and Monitor Deployments From Slack

Virtual Reality, Augmented Reality, and ERP

ভার্চুয়াল রিয়েলিটি, অগমেন্টেড রিয়েলিটি এবং ইআরপি

Virtual Reality, Augmented Reality und ERP

Realidad virtual, realidad aumentada y ERP

Réalité virtuelle, réalité augmentée et ERP

आभासी वास्तविकता, संवर्धित वास्तविकता और ईआरपी

仮想現実、拡張現実、ERP

가상 현실, 증강 현실 및 ERP

Realidade Virtual, Realidade Aumentada e ERP

Виртуальная реальность, дополненная реальность и ERP

Sanal Gerçeklik, Artırılmış Gerçeklik ve ERP

Thực tế ảo, thực tế tăng cường và ERP

虚拟现实、增强现实和 ERP

Let's learn about via these 70 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Statistics /Learn Repo 1. The State of Vue 2022: What Has Changed In The Last 12 Months Check the latest statistics on the usage of Vue and learn why this framework is growing in popularity. 2. Over 60% of Writers Already Use AI in Their Writing Workflow Hackernoon polled readers on whether they would use AI tools for their writing/copywriting workflow. Nearly 70% are open to the idea. 3. How to Install RStudio on the WSL System If you are using Windows and don’t want to use the RStudio client on the Windows side, this method will work perfectly. 4. Kannada-MNIST:A new handwritten digits dataset in ML town TLDR: 5. How Many Days of Your Life Have You Spent in an Uber? I've spent 12 days in Ubers over the last 3 years. Read this to find your own lifetime Uber stats. 6. AB Testing For Digital Products An overview of AB testing during the design of digital products like UX, digital marketing advertisements and software development. 7. What LinkedIn Tells Us About Developer Population in the World There are tons of articles about the number of developers in the world. But most of them either lack good methodology or simply borrow statistics from other resources. 8. Calculate Required Rate of Return With the Fama-French Three-Factor Model Investors are always evaluating the amount of risk they are willing to take for a certain expected return. Intuitively, the best investment maximizes the return 9. How to Predict News: Message Sequence Analysis & Digital Intuition We can be warned about upcoming events predominantly occurring under similar circumstances. 10. Granger Causality: Principle of Cause and Effect Explained ... in a world full of data, we can understand the impact with clever methods. Meet Granger causality. 11. How to Use Approximate Leave-one-out Cross-validation to Build Better Models How to use Approximate leave-one-out cross-validation for hyperparameter optimization and outlier detection for logistic regression and ridge regression 12. How to Implement Gaussian Blurs A Gaussian blur is applied by convolving the image with a Gaussian function. We’ll take the Gaussian function and we’ll generate an n x m matrix. 13. Everything you need to know about YCombinator S19 startups It is not a secret to anyone that YCombinator is the most successful accelerator in the world. They have made well over 2,538 investments. 14. Why AI is a Fear-Driven Discipline People are scared of AI. According to Genpact research: 15. Top 5 Tech Startup Trends in 2020 According to Statista, the global startup economy generates nearly $3 trillion. Startups have always been the driving force behind the world market, bringing new ideas, and transforming familiar business systems. Unfortunately, the economic crisis associated with Covid-19 has not spared this area. 16. The Hundred-Page Machine Learning Book [Review] I first ordered The Hundred-Page Machine Learning book back in May and am only just now finishing it up. In COVID-time, that was about 10 years ago. As you might have inferred, this book is NOT a quick read. What it lacks in easy reading, it makes up for in efficiency. This book swallows up the heavyweight mathematics textbooks and spits out a slim product no thicker than the width of my smartphone. From page one all the way to page 136, Andriy Burkov, the author, does not waste a single word in distilling the most practical concepts in machine learning. You read that right. It is MORE than 100 pages! Sounds like the book has some bias. Get it? Now get ready for my hundred-page book review. Just kidding. 17. What if Street Crime Statistics Matched Those of Cybercrime? If street crime statistics matched those of cybercrime, our world would resemble the Wild West. 18. Statistics Cheat Sheet: A Beginner's Guide to Probability and Random Events A beginner’s guide to Probability and Random Events. Understand the key statistics concepts and areas to focus on to ace your next data science interview. 19. Key 2022 Statistics in the No-Code/Low-Code Market We explore a low-code/no-code market poised for exponential growth in the coming years. 20. Size Does Matter: Global Control Group for a Bank Learn how to approach data-driven measurement properly. See what unexpected results we got in a bank and get insights for your own data analytics journey. 21. How Popular is Right-Wing Content on Facebook? Facebook has been criticized in the past because many believe they are allowing right-wing content to run rampant on the site. 22. Outlier Detection with Chi Square This is a simple method for outlier detection, the procedure basically is a Quantile of weibull distribution of the chi square test in python. 23. 3 Interesting NFT Statistics: How NFTs are Being Adopted Globally NFT ownership has increased throughout the globe, with Southeast Asian nations such as the Philippines, Thailand, and Malaysia leading the pack. 24. Correlation vs. Causation: Why Correlation Does Not Imply Causation The terms correlation and causation are quite often confused, however, they are not synonyms and this article specifies the main reasons why. 25. How to Create A  Funnel Chart In R Funnel Chart in R, A funnel chart is mainly used for demonstrates the flow of users through a business or sales process. 26. The Intuition Behind the “LIME” Concept in AI & ML A preambular article describing the fundamental principles & intuition behind the “LIME” concept in Artificial Intelligence & Machine learning. 27. Hinge Loss - A Steadfast Loss Evaluation Function for the SVM Classification Models in AI & ML Researchers use an algebraic acme called “Losses” in order to optimise the machine learning space defined by a specific use case. 28. Digital Workspaces: Hacking the Future of Work A look at how to engage in the future of work through digital workspaces 29. [Infographic] The State of Conversational AI in 2020 Conversational AI was always poised to take off in 2020. In fact, Gartner predicted that 80% of businesses would implement some sort of conversational interface by the end of this year. With the emergence of COVID-19 came compounded growth for the category - and I wanted to capture just how far we’ve come. So for the conversationally curious out there, I created this infographic that offers a clear depiction of where conversational AI stands at this very moment in time. 30. Beyond A/B Testing — Switchbacks and Synthetic Control Group Experimentation designing in the marketplace without AB-Testing using Synthetic Control Groups and Switchbacks. 31. Variance Inflation Factor - A Pertinent Statistical Metric for the Discernment of Multicollinearity 32. E-Commerce as the Cake, Not the Cherry on the Cake E-Commerce has spiraled due to the pandemic environment, leading to irreversibly enhanced online shopping. 33. The Concept Behind "Mean Target Encoding" in AI & ML An introductory article describing the concept & intuition behind “Mean Target Encoding” in AI&ML, its pros, cons and implementation with a real-time example. 34. Console #17: Japanese Pizza Toast and Turtles 01/12/2019 35. Top 7 Most Used Web Frameworks Among Developers Worldwide 2021 [Statistics] Top 7 Most Used Web Frameworks Among Developers Worldwide 2021 [Statistics] 36. A Single Speed Test is Fun — Hundreds of Them, May Actually be More Accurate Releasing the first internal build of the NordVPN apps that included NordLynx – our brand new protocol built on the backbone of WireGuard® – was an exciting moment for the team. Everyone started posting their speed test results on Slack and discussing the variance. While most of the time NordLynx outperformed other protocols, there were some cases with slightly worse speed results. 37. Why I Spent Years Writing a Children’s Book on Data Science I wrote a children's book on data science to inform others who have a hard time understanding data science and machine learning concepts, especially kids! 38. Applying Statistical Analysis to Intraday Forex Trading Using SQL Statistical Analysis, Intraday Forex Trading, Using SQL 39. Variance is More Than Just A Statistician's Buzzword Explaining real world applications and the philosophy of statistical variance through finance, investing, and gambling. 40. CLIP: An Innovative Aqueduct Between Computer Vision and NLP A rudimentary article describing the concept behind the "CLIP" algorithm in deep learning, its approach, implementation, scope & limitations. 41. 👨‍🔬️ Top 10 Data Scientist Skills to Develop to Get Yourself Hired List of Top 10 Data Scientist skills that guaranteed employment. As well as a selection of helpful resources to master these skills 42. How a Data Scientist Sees a Deck of Cards The Data Scientist Creativity Paradox 43. 12 Best Pre-Installed R Datasets Commonly Used for Statistical Analysis R programming is mostly used in statistical analysis and ML.
This article looks at the Best Pre-Installed R Datasets Commonly Used for Statistical Analysis. 44. Radial Basis Functions: Types, Advantages, and Use Cases An introductory article explaining the basic intuition, mathematical idea & scope of radial basis function in the development of predictive machine learning. 45. Use the 80/20 Rule with Moderation The 80/20 rule, a.k.a. Pareto principle, has been perpetuated along the lines: "80% of the effects come from 20% of the causes." Different cases where the rule emerges have been studied, in the last century, by great personalities such as Vilfredo Pareto (land ownership in Italy), George Kingsley Zipf (word frequency in Languages), and Joseph M. Juran (quality management in industries). Working as a Data Scientist, I have seen enough of the 80/20 rule being invoked in business meetings followed by a round of applause 👏👏👏. Also, I have read numerous LinkedIn posts alike. Most times, it is just a reckless stretch of the rule. But what is the danger here, if any? After all, profits matter more than mathematical and statistical rigor. 46. TikTok's Engagement Rate is an Average of 5.96% in 2022 Boost your social media strategies for 2022 by knowing the most important up-and-coming TikTok marketing trends and engagement stats. 47. How to Use Psychological Tricks to Bring Numbers to Life It’s easy to visualize placing 10 chairs in a room, but it’s difficult to visualize 1,000 chairs. In order to acquire an accurate frame-of-reference, most of us would need to start by sketching out a diagram. Understanding this and applying it to business, the last thing you want is for your customer to have to hunt down a pen, paper and calculator in order to understand your numerically-based product features - don’t assign homework. Captivate customer attention by applying these clever ways to convert numbers into things people care about. 48. Use Up-Sampling and Weights to Address Imbalance Data Problem Have you worked on machine learning classification problem in the real world? If so, you probably have some experience with imbalance data problem. Imbalance data means the classes we want to predict are disproportional. Classes that make up a large proportion of the data are called majority classes. Those that make up a smaller portion are minority classes. For example, we want to use machine learning models to capture credit card fraud, and fraudulent activities happens approximately 0.1% out of millions of transactions. The majority of regular transactions will impede the machine learning algorithm to identify patterns for the fraudulent activities. 49. Why Algorithmic Fairness is Elusive In 2016, Google photos classified a picture of two African-Americans as “gorillas.” Two years later, Google had yet to do more than remove the word “gorillas” from its database of classifications. In 2016, it was shown that Amazon was disproportionately offering one-day shipping to European-American consumers. In Florida, algorithms used to recommend detention and parole decisions on the basis of risk of recidivism were shown to have a higher error rate among African-Americans, such that African-Americans were more likely to be incorrectly recommended for detention who would not go on to re-offend. When translating out of a language with gender-neutral pronouns, and into languages with gendered pronouns, Google’s word2vec neural network injects gender stereotypes into translations, such that pronouns become “he” when in conjunction with “doctor” (or “boss,” “financier,” etc.) but become “she” when translated in conjunction with “nurse” (or “homemaker,” or “nanny,” etc.). 50. How to Retrieve Player Stats from the NHL's undocumented REST API It's that time of year again. Summer is coming to an end, Autumn is around the corner, and the NHL season is about to begin. 51. The Importance of Hypothesis Testing Hypothesis tests are significant for evaluating answers to questions concerning samples of data. 52. Detecting Changes in COVID-19 Cases with Bayesian Models Bayesian change point model to estimate the date that the number of new COVID-19 cases starts to flatten in different countries. 53. 3 Data Distributions for Counts in Layman’s Terms Counts are everywhere, so no matter your background, these data distributions will come in handy. 54. How I Broke Into Data Science A software engineer’s journey into data science at Yelp and Uber 55. Who even reads HackerNoon? You, obviously. And millions of people from around the world. What audience are you advertising to? Who are you writing for? Learn more about our readers here. 56. Numbers Don't Lie But They Are Easily Misinterpreted All The Time therefore a working compromise between these 2 extremes should be found on a case-by-case basis 57. Model Calibration in Machine Learning: An Important but Inconspicuous Concept A prelusive article comprehending the concept behind model calibration, its importance and usage in machine learning model development. 58. The Notions behind “Model-Based” and “Instance-Based” Learning in AI & ML A prelude article elucidating the fundamental principles and differences between “Model-based” & “Instance-based” learning in the branches of Artificial Intelligence & Machine learning. 59. Random: Meaning in Everyday Life and in Science “That’s so random!” Common phrase used to express something is unexpected or without a pattern. Does random mean something different in science? 60. 40% Americans Do Not Know What Affects Their Credit Score Your customers’ credit score is one of the most important numbers of their financial lives. This three-digit number is the most used credit scoring model by lenders for evaluating a borrower's creditworthiness or the likelihood that they’ll repay the money. 61. Making Sense of Bitcoin's Volatility Clustering and How To Take Advantage of it In 2019, Bitcoin's (BTC) volatility was erratic. On one day alone, the price of bitcoin changed by over 40%. However, for most days, the change in price hovers around 1%-2%. The purpose of this article is to investigate the nature of BTC's volatility and see what kind of strategies are suited best to take advantage of it. 62. [Dev Update] Hacker Noon + Google Analytics = Happy Authors Austin here, your friendly neighborhood software engineer from Hacker Noon, with some exciting news! We are pleased as punch to announce that contributing writers can now see pageviews and total time reading for all stories published with Hacker Noon since we began in 2016.  How cool is that? Previously our stats page was only accessible for recent story performance. 63. A Programmer's Guide to Crack 'Twice the Work, Half the Time' Code Modern methods of software measurement do not provide a strong base for continuous improvement. This article tries to fill this gap. 64. Statistics Show AI Adoption and Investment has Risen Rapidly in the Past 2 Years The concept of artificial intelligence as a non-human intelligence originated in the 1950s, but no one then could have imagined what success AI would achieve in the 2020s. In just 70 years, we have had bots that can learn, solve complex computational problems, write related texts, generate images and music, and analyze tons of information in seconds. 65. Breaking Down Secretary Problem What did you think of when you had a crush on someone? Did you fantasize about marriage with him/her? When you were in some serious relationship, did you plan marriage with your partner? How did the relationship turn out? Some relationships turn into a marriage, and some don’t. Hearing stories of many friends, I see extremely few people being in a relationship (and later marrying) with only one person whole over their life. 66. Key Application Performance Metrics From the Viewpoint of a Statistician-Turned-Developer You've just released your new app into the wild, live in production. Success! Now what? Your job is done, right? Wrong. Now that you've deployed your code, it's time to monitor it, collect data, and analyze your metrics. 67. #CorrelateThis - The Neural Activity of Mice Indicates Cryptocurrency Price Fluctuations In his research, Gvido reported the discovery of neurons that showed a neural correlation to the price fluctuations of the main cryptocurrencies! 68. These Are The Secret Weapons of Fake News Modern fake news has evolved into a complex organism, carefully designed to hide its deceptive mechanisms from any potential victim. But although the fake news field has grown into every possible digital channel, the truth is that at its core, in order to be effective, it still relies on exploiting our most basic human characteristics. 69. Simple Tips For A Successful Application Performance Monitoring You finally went live, congratulations! Now what? 70. Quantifying Variability: Variance, Standard Deviation, and Coefficient of Variation There are many ways to quantify variability, however, here we will focus on the most common ones: variance, standard deviation, and coefficient of variation. In the field of statistics, we typically use different formulas when working with population data and sample data. Thank you for checking out the 70 most read stories about Statistics on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

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Gartner's recent recognition of cloud development environments (CDEs) in its for Emerging Technologies marks a significant moment, underscoring the disruptive potential of this swiftly advancing technology. Hype Cycle What are CDEs, and why are they gaining momentum? This article delves into the emergence of CDEs, the innovations driving their adoption, and their potential future as foundational components in the software development lifecycle. Understanding Gartner Hype Cycles Annually, Gartner's Hype Cycle report highlights emerging technologies predicted to have a transformative impact on businesses over the next 5-10 years. The model traces technologies through five phases: - The debut of a technology. Innovation Trigger - Early publicity creates inflated projections and unrealistic hopes. Peak of Inflated Expectations - Interest declines as experiments fail to deliver. Trough of Disillusionment - The technology's capabilities become clearer as real-world use cases surface. Slope of Enlightenment - Broad adoption occurs as the technology proves its value. Plateau of Productivity Gartner's inclusion of a technology in its Hype Cycle signifies its substantial disruptive potential. Previous entries like Big Data, AI, and IoT have moved from early hype to become integral parts of businesses and society. The inclusion of cloud development environments in indicates its growing momentum and potential for mainstream adoption in the coming years. Gartner's top 25 emerging technologies for 2023 Exploring Cloud Development Environments Gartner has previously identified browser-based development environments as a key emerging technology in its Hype Cycle reports. They updated the terminology to cloud development environments this year, highlighting this disruptive shift in software development. Developers have traditionally worked locally, using tools and frameworks installed on their machines. However, managing dependencies and versions across teams became increasingly difficult as software complexity increased. CDEs arose to simplify this process by providing pre-configured, cloud-based development environments accessible via browser. CDEs include the operating system, programming languages, frameworks, dependencies, and tools required to code, test, and run an application. This environment is provisioned on demand and can be accessed remotely via a browser-based IDE or locally via integration with tools such as Visual Studio Code. Containerization technologies like are used by leading CDE providers such as Gitpod, GitHub Codespaces, Daytona, Codeanywhere, and Coder to optimize portability and efficiency. Docker The terminology change reflects the maturation of cloud-native development environments. Key Advantages Fueling CDE Adoption Several key factors explain the rising popularity of cloud development environments: - The team codes in identical, disposable cloud environments, eliminating compatibility issues and allowing seamless context switching. Consistent and portable environments - New developers can start working instantly in a pre-configured environment, reducing friction. Streamlined onboarding - Workspaces operate in secure, ephemeral containers isolated from each other, limiting potential vulnerabilities. Isolation and security - CDEs enable seamless sharing of environments for collaborative coding and debugging. Some even allow simultaneous editing. Collaboration - Developers can quickly switch languages, tools, and dependencies by spinning up new environments, and supporting polyglot projects. Flexibility - Resources scale dynamically based on computational needs, eliminating capacity constraints. Scalability - Workspaces persist in the cloud, enabling uninterrupted coding from any location or device, crucial for distributed teams. Business continuity These attributes align perfectly with the demands of modern software development, accounting for the rising interest in CDEs. Why Gartner Recognizes CDEs as an Emerging Technology Gartner's classification of CDEs as an emerging technology set for major near-term growth hinges on several factors: - As cloud infrastructure becomes ubiquitous, businesses are more open to cloud-native development workflows. Accelerating cloud adoption - Modern web and mobile apps rely on diverse languages, frameworks, and microservices, challenging to manage locally. Increasing stack complexity - Developers work across multiple projects using inconsistent stacks. CDEs simplify this context switching. Demand for portability - Built-in Git integrations align tightly with source-based workflows. Repository-centric workflows - Remote and hybrid work necessitate development environments accessible from anywhere, which CDEs enable. Shift to distributed teams - Isolated workspaces limit attack surfaces and prevent vulnerabilities from spreading. Need for enhanced security - Consistent environments, configurations, and dependencies powered by infrastructure-as-code increase efficiency. Standardization Gartner predicts continued acceleration as these factors become increasingly relevant across industries. Innovations Unlocked by Cloud Development Environments Cloud development environments also provide a flexible foundation for ongoing feature innovation, such as: - Co-editing, shared terminals, and streaming previews enable seamless teamwork without disrupting flow. Integrated collaboration - Automated provisioning and configuration removes tedious setup, allowing developers to start coding within minutes. Instant workspaces - Insights into developers' use of tools and navigation of workflows optimize efficiency. Developer productivity analytics - Repeatable processes for testing, building, deploying, and releasing software can be embedded and centrally managed as code. Built-in automation - Integration with productivity tools like Slack, Jira, and GitHub provides a streamlined experience. Unified workflow - Workspaces auto-scale compute resources to meet development, testing, and production demands. Lifecycle scalability - Consistent environment configuration allows seamless switching across projects and teams to increase alignment. Context portability Leading CDE providers continue to innovate quickly to maximize flexibility, productivity, and velocity. Evolution and Current Adoption Although CDE adoption is still in the early mainstream phase, usage continues to grow rapidly as developers experience benefits firsthand. Several tech giants are also developing internal CDE platforms to power their development workflows. For instance, built an internal CDE called to optimize productivity and consistency, created their internal platform to standardize their development environment, and developed their CDE focused on enabling collaboration at scale. Uber Devpod Spotify Backstage Stripe Devbox These internal investments by industry leaders underscore the immense value of CDEs. They are paving the way for the future of standardized development environments. Other independent providers like Gitpod and Daytona have experienced surging interest from forward-thinking organizations. Use within regulated industries remains limited due to security considerations but is expanding. Open standards around Devfiles and Dev Containers are also driving adoption by preventing vendor lock-in. Innovation and adoption continue to accelerate as developers flock to CDEs. The Importance of Security As development environments shift to the cloud, security becomes a paramount consideration. Standardized development environments offer key security advantages: - Ephemeral workspaces operate in separate containers isolated from hosts and each other. Isolation - Strict permissions limit workspace access and prevent elevation. Least privilege - Network traffic is encrypted both in transit and at rest. Encryption - Centralized monitoring and logging provide enhanced visibility. Observability - Solutions can adhere to standards like SOC2, ISO 27001, and GDPR. Compliance - Multi-tenant management planes are isolated from workspaces. Hardened infrastructure The secure-by-design architecture and advanced security capabilities of standardized development environments provide enterprise-grade protection without compromising agility and developer velocity. The Future of Standardized Development Environments Cloud development environments are evolving into integrated that encapsulate end-to-end application lifecycles. standardized development environments (SDEs) SDE platforms will provide guardrails and golden paths to accelerate development while allowing customization and freedom. Templated configurations will enable governance and oversight for enterprise IT. Automation and workflow integrations will eliminate inefficiencies and coordination hurdles. The unique focus of these environments extends the advantages of CDEs deeper across the software delivery lifecycle: - A consistent environment across development stages avoids mismatches and team coordination overhead. Unified experience - Templates and automation codify optimal patterns tailored to specific stacks and apps. Embedded best practices - Standardization and transparency into changes and configurations foster closer team alignment. Shared understanding - The flexibility to install extensions and personalize setups within guardrails boosts productivity. Developer autonomy - Integrated tools like co-editing, terminals, and previews keep developers in flow. Frictionless collaboration - Workspaces auto-scale compute for development, testing, staging, and production without reconfiguration. End-to-end scaling - Instantly recreate disposable and pre-configured environments with a single click. Blazing fast setup This hybrid, standardized approach, combining the best of local and cloud-based technologies, represents the future of software development environments. The Road Ahead Gartner's recognition of cloud development environments as an emerging technology on the rise has validated the tremendous potential of this disruptive shift. By providing consistent, collaborative, and portable environments that break down silos and accelerate workflows, CDEs address pressing needs for modern development teams. We can expect leaders and newcomers in this space to continue innovating to help tech leaders and developers maximize productivity, increase stability, and deliver higher-quality digital solutions. The future of CDEs is bright, and the most exciting innovations still lie ahead.

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