This Deep Learning Full Course video will help you understand and learn Deep Learning & Tensorflow in detail. This Deep Learning Tutorial is ideal for both beginners as well as professionals who want to master Deep Learning Algorithms.
Below are the topics covered in this Deep Learning tutorial video:
3:11 What is Deep Learning
3:55 Why Artificial Intelligence?
5:48 What is AI?
6:53 Applications of AI
8:43 Machine Learning
10:28 Types of Machine Learning
10:33 Supervised Learning
11:43 Unsupervised Learning
13:08 Reinforcement Learning
14:38 Limitations of Machine Learning
16:08 Deep Learning to the Rescue
19:28 What is Deep Learning?
22:58 Deep Learning Example
24:28 Deep Learning Applications
25:48 Deep Learning Tutorial
27:08 Understanding Deep Learning With an Analogy
29:58 How Deep Learning works?
31:12 Why We need Artificial Neuron?
32:58 Perceptron Learning Algorithm
36:13 Types of Activation Functions
41:33 Single Layer Perceptron Use-case
42:33 What is TensorFlow?
44:18 Tensorflow Code Basics
49:08 TensorFlow Example
59:13 What is a Computational Graph?
1:27:08 Limitations of Single Layer Perceptron
1:28:08 Multilayer Perceptron
1:29:18 How it works?
1:29:23 What is Backpropagation?
1:30:23 Backpropagation Learning Algorithm
1:34:43 Multilayer Perceptron Use-case
1:37:48 Top 8 Deep Learning Frameworks
1:38:18 Chainer
1:39:18 CNTK
1:40:48 Caffe
1:42:28 MXNet
1:43:33 Deeplearning4j
1:45:23 Keras
1:46:58 PyTorch
1:48:23 TensorFlow
1:50:23 TensorFlow Tutorial
1:50:43 Rock or Mine Prediction Use-case
1:52:53 How to Create This Model?
1:54:13 What are Tensors?
1:54:38 Tensor Rank
1:55:58 What is TensorFlow?
2:02:28 Graph Visualization
2:05:10 Constant, Placeholder & Variables
2:08:55 Creating A Model
2:17:06 Reducing The Loss
2:18:31 Batch Gradient Descent
2:22:01 Implementing Rock or Mine Prediction Use-case