Course Content
Machine Learning
Complete course on machine learning/deep learning.
0/20
1. Introduction to Machine Learning
01:18:04
2. Supervised Learning, Linear Regression
01:09:41
3. Logistic Regression and Regularization
01:11:24
4. Neural Networks
01:13:39
5. Deep Learning
01:07:52
Lecture 1 | Machine Learning (Stanford)
01:19:14
Lecture 2 | Machine Learning (Stanford)
01:12:27
Lecture 3 | Machine Learning (Stanford)
01:20:26
Lecture 10 | Deep Learning (Stanford)
01:17:33
Lecture 11 | Detection and Segmentation (Stanford)
01:18:46
But what is a Neural Network? | Deep learning, chapter 1
19:13
Gradient descent, how neural networks learn | Deep learning, chapter 2
21:00
What is backpropagation really doing? | Deep learning, chapter 3
13:54
Machine Learning Basics | What Is Machine Learning? | Introduction To Machine Learning
41:55
Machine Learning Full Course – Learn Machine Learning 10 Hours
10:23:13
Tensorflow 2.0 Complete Course – Python Neural Networks for Beginners
02:07:00
PyTorch Tutorial for Deep Learning Researchers
01:01:29
Deep Learning Crash Course for Beginners
01:12:41
Introduction to Deep Learning: Machine Learning vs Deep Learning
03:49
A friendly introduction to Deep Learning and Neural Networks
14:29
Machine Learning & Deep Learning

This lecture covers 4. Neural Networks with theoretical foundations and practical applications. Part of MIT’s Machine Learning course series. Credit: MIT OpenCourseWare (YouTube/UCEBb1b_L6zDS3xTUrIALZOw)

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