<h1>Machine Learning with JS: Regression Tasks (Math + Code)</h1>
<p>Dive into the world of machine learning with <strong>Machine Learning with JS: Regression Tasks (Math + Code)</strong>. This course offers a focused look at linear regression, blending theoretical knowledge with hands-on coding to teach you how to build and apply linear regression models using JavaScript.</p>
<h2>What You Will Learn:</h2>
<ul>
<li><strong>Core Principles of Linear Regression</strong>: Begin with the fundamentals of linear regression and expand into multiple regression techniques. Discover how these models can predict future outcomes based on past data.</li>
<li><strong>Hands-On Coding</strong>: Engage directly with practical coding examples, utilizing JavaScript. You'll use Node.js for the computational aspects and React.js for dynamic data visualization.</li>
<li><strong>Simplified Mathematics</strong>: We make the essential math behind the models accessible, focusing on concepts that allow you to understand and implement the algorithms effectively.</li>
<li><strong>Project-Based Learning</strong>: Build a React application from scratch that not only plots data but also computes regression parameters and visualizes these computations in real-time. This hands-on approach will help solidify your learning through actual development experience.</li>
<li><strong>Real-World Applications</strong>: Learn to forecast real-world outcomes using the models you build. Understand the importance of residuals and how to quantify model accuracy with statistical measures such as R-squared, Mean Absolute Error (MAE), and Mean Squared Error (MSE).</li>
<li><strong>Advanced Topics in Depth</strong>: Go beyond basic regression with sessions on handling complex data types through multiple regression analysis, matrix operations, and model selection techniques.</li>
</ul>
<h2>Course Structure:</h2>
<p>This course includes over 80 detailed video lectures that guide you through every step of learning machine learning with JavaScript:</p>
<ul>
<li><strong>Introduction and Setup</strong>: Start with an overview of the necessary tools and configurations. Understand the foundational terms and concepts in regression.</li>
<li><strong>Interactive Exercises</strong>: Each new concept is paired with practical coding exercises that reinforce the material by putting theory into practice.</li>
<li><strong>In-Depth Projects</strong>: Apply what you've learned in extensive, real-world projects. Predict salary ranges based on job data or estimate car prices with sophisticated regression models.</li>
</ul>
<h2>Why Choose This Course?</h2>
<ul>
<li><strong>Targeted Learning</strong>: We focus on linear regression to provide a thorough understanding of one of the most common machine learning techniques.</li>
<li><strong>Practical JavaScript Use</strong>: By using JavaScript, a language familiar to many developers, this course demystifies the process of integrating machine learning into web applications and backend services.</li>
<li><strong>Project-Driven Approach</strong>: The projects are designed to reflect real industry problems, preparing you for technical challenges in your career.</li>
</ul>


Explore practical coding, data analysis, and visualization with JavaScript and React JS, plus get Math background.

Machine Learning Primer with JS: Regression (Math + Code)

What students learn

Requirements

Target Audience

Social

Machine Learning Primer with JS: Regression (Math + Code)

Course information

What students learn

Requirements

Target Audience

Social