TensorFlow Full Course video is a complete guide to Deep Learning using TensorFlow. It covers in-depth knowledge about Deep Leaning, Tensorflow & Neural Networks. Below are the topics covered in this TensorFlow tutorial:
2:07 Artificial Intelligence
2:21 Why Artificial Intelligence?
5:27 What is Artificial Intelligence?
5:55 Artificial Intelligence Domains
6:14 Artificial Intelligence Subsets
11:17 Machine Learning
12:32 Types of Machine Learning
12:39 Machine Learning Use Case
15:55 Supervised Learning
18:50 Types of Supervised Learning
20:17 Use Case 2
21:28 Linear Regression
26:34 Linear Regression Demo
38:39 Regression Application
40:14 Building Logistic Regression Model
40:24 Logistic Regression Use Case
46:55 Analysing Performance Of The Model
49:40 Calculating The Accuracy
51:31 Logistic Regression Demo
1:01:38 Clustering Use Case
1:05:12 How Clustering works?
1:05:12 Initialization
1:06:07 Cluster Assignment
1:07:37 Move Centroid
1:08:27 Optimization
1:08:32 Convergence
1:09:22 How to find optimal solution?
1:09:30 Choosing the number of cluster
1:16:35 Reinforcement Learning
1:17:35 Limitation of Machine Learning
1:22:00 How Deep Learning Solves the Issue?
1:25:05 What is Deep Learning?
1:26:35 Applications of Deep Learning
1:29:14 What is a Tensor?
1:29:48 Rank of Tensors
1:32:13 Shape of a Tensor
1:33:58 What is TensorFlow?
1:35:38 TensorFlow Code Basics
1:36:09 TensorFlow Basic Demo
2:00:33 Activation or Transformation Function
2:01:28 Linear
2:02:18 Unit Step
2:03:23 Sigmoid
2:04:23 Tanh
2:05:18 ReLU
2:05:53 Softmax
2:07:03 Activation Function Demo
2:10:43 How Neuron Works?
2:13:08 What is a Perceptron?
2:15:53 Role of Weights & Bias
2:16:18 Perceptron Example
2:22:23 Training a Perceptron
2:22:48 Perceptron Learning Algorithm
2:26:08 Training Network Weights
2:39:43 Reducing The Loss
2:43:18 Perceptron Learning Algorithm Demo
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