Deep Learning Crash Course for Beginners

>> YOUR LINK HERE: ___ http://youtube.com/watch?v=VyWAvY2CF9c

Learn the fundamental concepts and terminology of Deep Learning, a sub-branch of Machine Learning. This course is designed for absolute beginners with no experience in programming. You will learn the key ideas behind deep learning without any code. • You'll learn about Neural Networks, Machine Learning constructs like Supervised, Unsupervised and Reinforcement Learning, the various types of Neural Network architectures, and more. • ✏️ Course developed by Jason Dsouza. Check out his YouTube channel: / jasmcaus • ⭐️ Course Contents ⭐️ • ⌨️ (0:00) Introduction • ⌨️ (1:18) What is Deep Learning • ⌨️ (5:25) Introduction to Neural Networks • ⌨️ (6:12) How do Neural Networks LEARN? • ⌨️ (12:06) Core terminologies used in Deep Learning • ⌨️ (12:11) Activation Functions • ⌨️ (22:36) Loss Functions • ⌨️ (23:42) Optimizers • ⌨️ (30:10) Parameters vs Hyperparameters • ⌨️ (32:03) Epochs, Batches Iterations • ⌨️ (34:24) Conclusion to Terminologies • ⌨️ (35:18) Introduction to Learning • ⌨️ (35:34) Supervised Learning • ⌨️ (40:21) Unsupervised Learning • ⌨️ (43:38) Reinforcement Learning • ⌨️ (46:25) Regularization • ⌨️ (51:25) Introduction to Neural Network Architectures • ⌨️ (51:37) Fully-Connected Feedforward Neural Nets • ⌨️ (54:05) Recurrent Neural Nets • ⌨️ (1:04:40) Convolutional Neural Nets • ⌨️ (1:08:07) Introduction to the 5 Steps to EVERY Deep Learning Model • ⌨️ (1:08:23) 1. Gathering Data • ⌨️ (1:11:27) 2. Preprocessing the Data • ⌨️ (1:19:05) 3. Training your Model • ⌨️ (1:19:33) 4. Evaluating your Model • ⌨️ (1:19:55) 5. Optimizing your Model's Accuracy • ⌨️ (1:25:15) Conclusion to the Course • -- • Learn to code for free and get a developer job: https://www.freecodecamp.org • Read hundreds of articles on programming: https://freecodecamp.org/news

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