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React with its ecosystem is a flexible framework. You can choose your libraries to complement your React core. The following article will give you an opinionated approach to select from these libraries to build a sophisticated React application.

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The article guides you through implementing Machine Learning in JavaScript. The article can be used as introduction to machine learning in JavaScript and as entry point to a whole blog post series.

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I am doing React + Redux for quite some time now. My learnings are subjective, but I thought they may help people to learn or advance in React + Redux. Redux is not strictly coupled to React, but it happens to be that a lot of people are using both libraries in combination. The article is opinionated, maybe it doesn't match every time your thoughts, but I hope to get feedback on it to improve myself as well.

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A complete walkthrough to learn about Firebase authentication in React. The guide gives you the perfect boilerplate as outcome for user authentication and authorization in React.

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The article guides you through the implementation of a neural network in JavaScript with Google's deeplearn.js library. In general, it should show how machine learning can be achieved in JavaScript.

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The article guides you through implementing a logistic regression with gradient descent algorithm in JavaScript to solve a classification problem. You should read the article about linear regression with gradient descent before diving into logistic regression.

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The article guides you through implementing normal equation as alternative to gradient descent to solve a regression problem in JavaScript. You should learn about gradient descent before diving into this topic.

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The article guides you through implementing linear regression with gradient descent in a multivariate training set in JavaScript. It shows the vectorized implementation of the algorithm and performs feature scaling by using standardization before applying the learning algorithm.

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The article guides you through implementing a vectorized implementation of gradient descent for a regression problem in JavaScript. You should be familiar with gradient itself by reading the introductory article before diving into this topic.

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When using gradient descent as learning algorithm for a regression problem, there are several ways to improve it. In the beginning, it is often unclear how to optimize it. This article shows it by choosing the right learning rate and initial parameters, applying feature scaling and vectorization.

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