Next Glass

My stack to build a SaaS with Next JS and serverless backend. A full-stack react SaaS boilerplate template to kickstart any project.

The Tech Stack of a Solo-Developer to build a SaaS With React and AWS

Predict BJP Congress Sentiment using Deep Learning

Sentiment Analysis using Deep Learning techniques with India Elections 2019 — A Case study

Technological evolution has changed the landscape, everything which we feel and hear today is revolving around some of the modern technology. This technology involves Artificial Intelligence, big data, cloud computing, data science, and much more, which has changed the landscape to a great extent. To integrate this technology, many of the IT professionals are finding and implementing the trajectory of today's modern technologies.

Hadoop for Hoops: Explore the Whole Ecosystem and to Know How It Really Works

Text classification is task of categorising text according to its content. It is the fundamental problem in the field of Natural Language Processing(NLP). More general applications of text classifications are in email spam detection, sentiment analysis and topic labelling etc.

Text Classification in iOS using tensorflowlite [A How-To Guide]

With the problem of Image Classification is more or less solved by Deep learning, <strong><em>Text Classification is the next new developing theme in deep learning</em>. </strong>For those who don’t know, Text classification is a common task in natural language processing, which transforms a sequence of a text of indefinite length into a category of text. How could you use that?

What Kagglers are using for Text Classification

This all started when I was asked to speak at an <a href="http://www.aiff.world/" target="_blank">AI FinTech</a> forum in July. It represented a great opportunity for me to talk about <a href="https://machinebox.io/?utm_source=Medium&amp;utm_medium=Post&amp;utm_campaign=Predicting%20the%20stock%20market" target="_blank">Machine Box</a> to a new audience. But there was a problem. I don’t know anything about financial technology!

I spent 20 minutes trying to predict the stock market with AI — these are my results

Machine Learning Practitioners have different personalities. While some of them are “I am an expert in X and X can train on any type of data”, where X = some algorithm, some others are “Right tool for the right job people”. A lot of them also subscribe to “Jack of all trades. Master of one” strategy, where they have one area of deep expertise and know slightly about different fields of Machine Learning. That said, no one can deny the fact that as practicing Data Scientists, we will have to know basics of some common machine learning algorithms, which would help us engage with a new-domain problem we come across. This is a whirlwind tour of common machine learning algorithms and quick resources about them which can help you get started on them.

Ten Machine Learning Algorithms You Should Know to Become a Data Scientist

Building good end to end tests is hard. Having good end to end tests is wonderful. How do you get from the former to the latter?

End to End Testing in One Short Second with Dart

Next Glass powers the alcoholic beverage industry through innovative software \u0026 technology, world-class experiences, and unparalleled content that reflects our unique and enthusiastic community

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