FeatureBear

This paper presents an opensource toolkit intended primarily for ecologists and computer-vision/machine-learning researchers for wildlife re-identification.

WildlifeDatasets: an Open-source Toolkit for Animal Re-identification: Ablation Studies

In this paper, researchers introduce VEATIC dataset for human affect recognition, addressing limitations in existing datasets, enabling context-based inference.

VEATIC: Familiarity and Enjoyment Ratings & References

Discover how Scrutor enhances dependency injection in C# applications.

3 Simple Tips For Dependency Injection Using Scrutor in C#

This section delves into the field of FL, a method created to produce accurate models while protecting the privacy of people and institutions.

Collaborative and Privacy-Preserving Model Training: The Pros and Cons

Learn everything you need to know about Environment via these 49 free HackerNoon stories.

49 Stories To Learn About Environment

Learn everything you need to know about Terraform via these 51 free HackerNoon stories.

51 Stories To Learn About Terraform

Learn everything you need to know about Infrastructure As Code via these 46 free HackerNoon stories.

46 Stories To Learn About Infrastructure As Code

Learn everything you need to know about Code Quality via these 274 free HackerNoon stories.

274 Stories To Learn About Code Quality

I've reviewed how to deploy KubeCF on EKS, which gives you a nice, stable deployment of KubeCF, for cost. Now let's run KubeCF on your Mac for free(ish)!

How to Stop Giving Away Money to AWS by Running KubeCF with Kind on MacOS

In this article you will gain some insights about NFT Marketplaces on different chains.

A Brief Intro to NFT Marketplaces

“The advantage of feature branching is that each developer can work on their own feature and be isolated from changes going on elsewhere.” (FeatureBranch)

From “Feature branches” to “Feature environments” with Terraform

<a href="https://hackernoon.com/tagged/continuous-integration"><strong>Continuous Integration</strong>(CI)</a> is not a new terminology in software development. It is known for making software development easier by providing rapid feedback and reducing integration problems.

Anti Patterns of Continuous Integration

A few years back it was widely known that Object Detection was a hard problem to solve. The comic below was just a few years back. Things have changed in this short time quite drastically.

Is Object Detection a Done Deal?

Experiments using Optimizely X’s Full Stack SDKs are typically implemented by using conditionals in your codebase to decide between feature variations. As experiments progress and clear winners from experimentation emerge this conditional code can create <a href="https://en.wikipedia.org/wiki/Technical_debt" target="_blank">technical debt</a>, once competing variations are no longer needed.

How the Factory Pattern Can Reduce Technical Debt

Last week, we took a step into the monadic world of parsing by learning about the <a href="https://hackage.haskell.org/package/attoparsec" target="_blank">Attoparsec</a>library. It provided us with a clearer syntax to work with compared to applicative parsing. This week, we’ll explore one final library: <a href="https://hackage.haskell.org/package/megaparsec" target="_blank">Megaparsec</a>.

Megaparsec: Same Syntax, More Features!

In <a href="https://www.mmhaskell.com/blog/2018/2/19/applicative-parsing-ii-putting-the-pieces-together" target="_blank">last week’s article</a> we completed our look at the <a href="https://hackage.haskell.org/package/regex-applicative" target="_blank">Applicative Parsing</a> library. We took all our smaller combinators and put them together to parse our Gherkin syntax. This week, we’ll look at a new library: <a href="https://hackage.haskell.org/package/attoparsec" target="_blank">Attoparsec</a>. Instead of trying to do everything using a purely applicative structure, this library uses a monadic approach. This approach is much more common. It results in syntax that is simpler to read and understand. It will also make it easier for us to add certain features.

Attoparsec: The Clarity of Do-Syntax

In <a href="https://www.mmhaskell.com/blog/2018/2/12/applicative-parsing-i-building-the-foundation" target="_blank">last week’s article</a>, we introduced the <a href="https://hackage.haskell.org/package/regex-applicative" target="_blank">Applicative parsing library</a>. We learned about the <code class="markup--code markup--p-code">RE</code> type and the basic combinators like <code class="markup--code markup--p-code">sym</code> and <code class="markup--code markup--p-code">string</code>. We saw how we could combine those together with applicative functions like <code class="markup--code markup--p-code">many</code> and <code class="markup--code markup--p-code">&lt;*&gt;</code> to parse strings into data structures. This week, we’ll put these pieces together in an actual parser for our Gherkin syntax. To follow along with the code examples, check out <a href="https://github.com/jhb563/GherkinParsing/blob/master/src/Parser.hs" target="_blank">Parser.hs</a> on the Github repository.

Applicative Parsing II: Putting the Pieces Together

<a href="https://mmhaskell.com/blog/2018/2/5/parsing-primer-gherkin-syntax" target="_blank">Last week</a> we prepared ourselves for parsing by going over the basics of the Gherkin Syntax. In this article and the next, we’ll be using the <a href="https://hackage.haskell.org/package/regex-applicative-0.3.3/docs/Text-Regex-Applicative.html#t:RE" target="_blank">applicative parsing</a> library to parse that syntax. This week, we’ll focus on the fundamentals of this library, and build up a vocabulary of combinators to use. We’ll make heavy use of the <code class="markup--code markup--p-code">Applicative</code> typeclass. If you need a refresher on that, check out <a href="https://mmhaskell.com/blog/2017/2/6/applicatives-one-step-further" target="_blank">this article</a>. As we start coding, you can also follow along with the examples on <a href="https://github.com/jhb563/GherkinParsing" target="_blank">Github here</a>! Most of the code here is in <a href="https://github.com/jhb563/GherkinParsing/blob/master/src/Parser.hs" target="_blank">Parser.hs</a>.

Applicative Parsing I: Building the Foundation

It's already challenging enough to create a website that is blazing fast, adheres to all the latest best practices and offers optimal experience for various network conditions and device types.

As the website and its codebase evolves over time, it can become even harder to maintain the desired user experience over time. To prevent UX deterioration, it’s often a good idea to place guardrails which ensure that crucial website elements, such as images, hold to a certain criteria. In this article, we are going to look at a robust mechanism which helps to steer your website in the right direction - an HTTP header called Feature Policies.

Feature/Permission Policies Overview

FeatureBearis in the Product Management Tools Industry

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Since n.d.

FeatureBear's stories on HackerNoon

WildlifeDatasets: an Open-source Toolkit for Animal Re-identification: Ablation Studies

VEATIC: Familiarity and Enjoyment Ratings & References

3 Simple Tips For Dependency Injection Using Scrutor in C#

Collaborative and Privacy-Preserving Model Training: The Pros and Cons

49 Stories To Learn About Environment

51 Stories To Learn About Terraform

46 Stories To Learn About Infrastructure As Code

274 Stories To Learn About Code Quality

How to Stop Giving Away Money to AWS by Running KubeCF with Kind on MacOS

A Brief Intro to NFT Marketplaces

From “Feature branches” to “Feature environments” with Terraform

Anti Patterns of Continuous Integration

Is Object Detection a Done Deal?

How the Factory Pattern Can Reduce Technical Debt

Megaparsec: Same Syntax, More Features!

Attoparsec: The Clarity of Do-Syntax

Applicative Parsing II: Putting the Pieces Together

Applicative Parsing I: Building the Foundation

Feature/Permission Policies Overview

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