<h1>Master Neural Networks: Build with JavaScript and React</h1>
<p>Welcome to <strong>Master Neural Networks: Build with JavaScript and React</strong>. This comprehensive course is designed for anyone looking to understand and build neural networks from the ground up using JavaScript and React.</p>
<h2>What You'll Learn:</h2>
<h3>Introduction to Neural Networks</h3>
<ul>
<li>Understand the basics of perceptrons and their similarities to biological neurons.</li>
<li>Learn how perceptrons work at a fundamental level.</li>
</ul>
<h3>Building a Simple Perceptron</h3>
<ul>
<li>Code a perceptron to classify simple objects (e.g., pencils vs. erasers) using hardcoded data.</li>
<li>Implement a basic perceptron from scratch and train it with sample inputs and outputs.</li>
<li>Draw graphs and explain the steps needed, including defining weighted sums and activation functions.</li>
</ul>
<h3>Perceptron for Number Recognition</h3>
<ul>
<li>Advance to coding a perceptron for number recognition using the MNIST dataset to identify if a number is 0 or not.</li>
<li>Train the perceptron using the MNIST dataset, optimizing weights and biases.</li>
<li>Learn techniques to calculate accuracy and handle misclassified data.</li>
<li>Save and export the trained model for use in web applications.</li>
</ul>
<h3>Parsing and Preprocessing MNIST Data</h3>
<ul>
<li>Learn to parse and preprocess MNIST data yourself.</li>
<li>Understand the file formats and the steps needed to convert image data into a usable format for training.</li>
</ul>
<h3>Building a Multi-Layer Perceptron (MLP)</h3>
<ul>
<li>Develop a more complex MLP to recognize digits from 0 to 9.</li>
<li>Implement training algorithms and understand backpropagation.</li>
<li>Explore various activation functions like ReLU and Softmax.</li>
</ul>
<h3>Practical Implementation with JavaScript and React</h3>
<ul>
<li>Integrate neural networks into web applications using JavaScript, React, and Node.js.</li>
<li>Build and deploy full-stack applications featuring neural network capabilities.</li>
<li>Create a React application to test and visualize your models, including drawing on a canvas and making predictions.</li>
</ul>
<h2>Course Features:</h2>
<ul>
<li>Step-by-step coding tutorials with detailed explanations.</li>
<li>Hands-on projects to solidify your understanding.</li>
<li>Graphical visualization of neural network decision boundaries.</li>
<li>Techniques to save and export trained models for real-world applications.</li>
<li>Comprehensive coverage from basic perceptrons to multi-layer perceptrons.</li>
</ul>


Build and integrate Neural Networks in Web Apps with JavaScript, React, and Node.js. From Scratch with Math Included.

Master Neural Networks: Build with JavaScript and React

What students learn

Requirements

Target Audience

Social

Master Neural Networks: Build with JavaScript and React

Course information

What students learn

Requirements

Target Audience

Social