Artículo: AMZ-B0F4D6P6KN

Machine Learning with JavaScript: Practical Guide to ML | Build 8 AI Applications | TensorFlow.js & Brain.js Projects

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JavaScript for Machine Learning: Harness the power of JavaScript-based libraries like TensorFlow.js, Brain.js, and ml5.js to create intelligent applications that run directly in the browser or on the server with Node.js.
Core ML Concepts: Understand key topics such as supervised and unsupervised learning, neural networks, deep learning, and reinforcement learning—all within the context of JavaScript development.
Hands-On Projects: Build eight real-world AI applications from scratch, including image classification, real-time object detection, a chatbot with natural language processing (NLP), speech-to-text conversion, and more.
Data Handling and Model Optimization: Learn essential techniques for data preparation, training ML models, optimizing their performance, and deploying them in web-based environments.
Performance Optimization: Discover strategies to accelerate your ML models using WebAssembly (WASM), WebGL for GPU acceleration, and more to run fast, scalable AI applications.
Build and deploy ML models in the browser and on the server with JavaScript.
Learn through hands-on projects that reinforce key concepts and boost your practical experience.
Work with real-world datasets and popular libraries to create intelligent applications.
Optimize performance and handle large datasets with ease using cutting-edge tools.
Access easy-to-follow, step-by-step guides that make complex machine learning concepts approachable.