Section 1 : INTRODUCTION AND COURSE OUTLINE
Lecture 1 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 2 About Certification
Lecture 3 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 4 ML, AI and DL 00:12:00 Duration
Lecture 5 Machine Learning Big Picture 00:08:15 Duration
Lecture 6 About Proctor Testing
Lecture 7 Whats New in TensorFlow 2 00:15:07 Duration
Lecture 8 What is Google Colab 00:05:08 Duration
Lecture 9 Google Colab Demo 00:07:17 Duration
Lecture 10 Eager Execution 00:10:30 Duration
Lecture 11 Keras API 00:06:56 Duration
Lecture 12 About Certification

Section 2 : REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS
Lecture 1 ANN and CNN - Part 1 00:17:48 Duration
Lecture 2 ANN and CNN - Part 2 00:08:13 Duration
Lecture 3 ANN and CNN - Part 3 00:13:33 Duration
Lecture 4 ANN and CNN - Part 4 00:05:33 Duration
Lecture 5 ANN and CNN - Part 5 00:10:54 Duration
Lecture 6 ANN and CNN - Part 6 00:05:56 Duration
Lecture 7 ANN and CNN - Part 7 00:16:24 Duration
Lecture 8 ANN and CNN - Part 8
Lecture 9 Project 1 - Solution Part 1 00:06:06 Duration
Lecture 10 Project 1 - Solution Part 2 00:12:33 Duration

Section 3 : TRANSFER LEARNING (TF HUB)
Lecture 1 What is Transfer learning 00:08:26 Duration
Lecture 2 Transfer Learning Process 00:10:10 Duration
Lecture 3 Transfer Learning Strategies 00:07:54 Duration
Lecture 4 ImageNet 00:08:35 Duration
Lecture 5 Transfer Learning Project 1 - Coding P1 00:09:51 Duration
Lecture 6 Transfer Learning Project 1 - Coding P2 00:14:32 Duration
Lecture 7 Transfer Learning Project 1 - Coding P3 00:10:17 Duration
Lecture 8 Transfer Learning Project 1 - Coding P4 00:11:25 Duration
Lecture 9 Transfer Learning Project 1 - Coding P5 00:08:02 Duration
Lecture 10 Transfer Learning Project 2 - Coding P1 00:05:23 Duration
Lecture 11 Transfer Learning Project 2 - Coding P2 00:07:14 Duration
Lecture 12 Transfer Learning Project 2 - Coding P3 00:09:35 Duration

Section 4 : AUTOENCODERS
Lecture 1 Autoencoders intuition 00:12:29 Duration
Lecture 2 Autencoders Math 00:14:49 Duration
Lecture 3 Linear Autoencoders vs 00:05:53 Duration
Lecture 4 Autoencoders Applications 00:10:16 Duration
Lecture 5 Variational Autoencoders (VARS) 00:08:21 Duration
Lecture 6 Autoencoders CNN Dimensionality Review 00:09:37 Duration
Lecture 7 Autoencoders Project 1 - Coding P1 00:09:48 Duration
Lecture 8 Autoencoders Project 1 - Coding P2 00:08:44 Duration
Lecture 9 Autoencoders Project 1 - Coding P3 00:09:10 Duration
Lecture 10 Autoencoders Project 1 - Coding P4 00:09:32 Duration
Lecture 11 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 12 Autoencoders Project 2 - Coding P1 00:12:03 Duration
Lecture 13 Autoencoders Project 2 - Coding P2 00:21:14 Duration

Section 5 : DEEP DREAM
Lecture 1 What is Deep Dream 00:13:25 Duration
Lecture 2 How does DeepDream Algo work
Lecture 3 Deep Dream Simpified 00:06:36 Duration
Lecture 4 Deep Dream Coding P1
Lecture 5 Deep Dream Coding P2 00:09:04 Duration
Lecture 6 Deep Dream Coding P3 00:05:51 Duration
Lecture 7 Deep Dream Coding P4 00:11:39 Duration
Lecture 8 Deep Dream Coding P5 00:19:18 Duration

Section 6 : GANs
Lecture 1 GANS intuition 00:10:51 Duration
Lecture 2 Discriminator and Generator Networks 00:13:39 Duration
Lecture 3 Let's put the Discriminator and Generator together 00:13:39 Duration
Lecture 4 GAN Lab 00:12:19 Duration
Lecture 5 GANs applications
Lecture 6 GANS Project 1 P1 00:08:09 Duration
Lecture 7 GANS Project 1 P2 00:10:53 Duration
Lecture 8 GANS Project 1 P3 00:04:00 Duration
Lecture 9 GANS Project 1 P4 00:05:38 Duration
Lecture 10 GANS Project 1 P5 00:12:57 Duration

Section 7 : RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs
Lecture 1 Recurrent Neural Networks Intuition 00:04:47 Duration
Lecture 2 RNN Architecture 00:09:17 Duration
Lecture 3 What makes RNN so special 00:06:51 Duration
Lecture 4 RNN Math 00:05:46 Duration
Lecture 5 Fun with RNN 00:07:07 Duration
Lecture 6 Vanishing Gradient Problem 00:12:19 Duration
Lecture 7 Long Short Term Memory LSTM
Lecture 8 RNN Project #1 - Part #1 00:08:18 Duration
Lecture 9 RNN Project #1 - Part #2 00:06:14 Duration
Lecture 10 RNN Project #1 - Part #3 00:05:44 Duration
Lecture 11 RNN Project #1 - Part #4 00:07:58 Duration

Section 8 : TENSORFLOW SERVING AND TENSORBOARD
Lecture 1 TF Serving Coding Part 1 00:09:11 Duration
Lecture 2 TF Serving Coding Part 2 00:07:50 Duration
Lecture 3 TF Serving Coding Part 3 00:12:18 Duration
Lecture 4 Tensorboard Example 1 00:12:23 Duration
Lecture 5 Tensorboard Example 2 00:09:21 Duration
Lecture 6 Distributed Strategy 00:03:10 Duration