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Deep Learning Crash Course for Beginners

Deep Learning Crash Course for Beginners

03:30 914,395 views

Practical Deep Learning for Coders: Lesson 1

Practical Deep Learning for Coders: Lesson 1

03:30 927,308 views

PyTorch for Deep Learning & Machine Learning – Full Course

PyTorch for Deep Learning & Machine Learning – Full Course

03:30 838,706 views

Learn PyTorch for deep learning in a day. Literally.

Learn PyTorch for deep learning in a day. Literally.

03:30 669,164 views

Understanding Deep Learning Research Tutorial - Theory, Code and Math

Understanding Deep Learning Research Tutorial - Theory, Code and Math

03:30 106,453 views

Machine Learning Explained in 100 Seconds

Machine Learning Explained in 100 Seconds

02:35 247,602 views

Practical Deep Learning for Coders - Full Course from fast.ai and Jeremy Howard

Practical Deep Learning for Coders - Full Course from fast.ai and Jeremy Howard

03:30 642,561 views

Machine Learning for Everybody – Full Course

Machine Learning for Everybody – Full Course

03:30 548,590 views

Building a neural network FROM SCRATCH (no Tensorflow/Pytorch, just numpy & math)

Building a neural network FROM SCRATCH (no Tensorflow/Pytorch, just numpy & math)

31:28 616,971 views

I Tried Coding a Neural Network to Identify Doodles

I Tried Coding a Neural Network to Identify Doodles

54:51 808,851 views

Lec 01. Introduction to Deep Learning

Lec 01. Introduction to Deep Learning

03:30 711,033 views

🎓 Featured Course Guide & Lesson Notes: Deep Learning Crash Course for Beginners

Top Result #1

Instructor: freeCodeCamp.org  |  Runtime: 03:30 mins  |  Students / Views: 914,395

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 work on Github: https://github.com/jasmcaus ❤️ Try interactive AI courses we love, right in your browser: https://scrimba.com/freeCodeCamp-AI (Made possible by a grant from our friends at Scrimba) ⭐️ 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 Key Highlights & Overview: Mastering <strong>Deep Learning Code Practice</strong> requires clear step-by-step guidance and practical hands-on visual demonstrations. Explore curated video courses, expert walkthroughs, and detailed lesson notes today on <strong>TutorTube</strong>.