๐ This video breaks down high-level concepts of artificial intelligence, machine learning, and deep learning.
๐ป You will learn how to practically apply these techniques using the tensorflow.js library and models in the browser.
๐ง The knowledge gained can be used to enhance web apps, such as classifying comment text and using sensors for real-time alerts.
๐ Chapter 2 introduces common terms, background of tensorflow.js, and different ways of leveraging machine learning.
๐ Chapter 2 sets up the foundation for deeper learning in the course.
๐ก Chapter 3 focuses on using pre-made machine learning models.
๐ก WebML course introduces easy-to-use machine learning models in JavaScript.
๐ Learn about the concept of tensors and how to load tensorflow.js models.
๐๏ธ Chapter 4 focuses on creating simple models like linear regression and perceptrons.
๐ฌ Explore more advanced techniques like convolutional neural networks for image classification.
๐ Chapter 5: Transfer learning is the art of using an existing model to learn something new and save time and money.
๐ป Chapter 6: Reusing machine learning models from Python in JavaScript to run them in the browser.
๐ฎ Chapter 7: Exploring future model architectures for inspiration.
๐ The video is about a breakdown of the WebML course.
๐ง The video provides further resources to investigate and ways to get involved in the tensorflow.js community.
๐ป๐๐ By applying the knowledge learned, viewers can become productive in machine learning and JavaScript.
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