Course Content
Subtitle Guide – Hướng dẫn thêm phụ đề
0/1
Set up subtitle for video – Hướng dẫn thêm phụ đề
01 – Welcome
0/4
Download Resource Files
001 Introduction
02:35
002 Outline and Perspective
06:49
003 How to Succeed in this Course
03:04
02 – Google Colab & Getting Setup
0/7
Download Resource Files
001 Where to get the code, notebooks, and data
04:29
002 Intro to Google Colab, how to use a GPU or TPU for free
12:33
003 Uploading your own data to Google Colab_part1
05:50
003 Uploading your own data to Google Colab_part2
05:50
004 Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn
11:00
005 Temporary 403 Errors
02:57
03 – Machine Learning Basics Review
0/15
Download Resource Files
001 What is Machine Learning
14:26
002 Code Preparation (Classification Theory)
15:59
003 Beginner’s Code Preamble
04:38
004 Classification Notebook_part1
11:10
004 Classification Notebook_part2
11:10
005 Code Preparation (Regression Theory)
07:19
006 Regression Notebook_part1
09:09
006 Regression Notebook_part2
09:09
006 Regression Notebook_part3
09:09
007 The Neuron
09:58
008 How does a model learn
10:54
009 Making Predictions
06:45
010 Saving and Loading a Model
04:28
011 Suggestion Box
03:10
04 – Artificial Neural Networks (ANN) Review
0/11
Download Resource Files
001 Artificial Neural Networks Section Introduction
06:00
002 Forward Propagation
09:40
003 The Geometrical Picture
09:43
004 Activation Functions
17:18
005 Multiclass Classification
08:41
006 How to Represent Images
12:36
007 Color Mixing Clarification
00:54
008 Code Preparation (ANN)
12:42
009 ANN for Image Classification
08:36
010 ANN for Regression
11:05
05 – Convolutional Neural Networks (CNN) Review
0/13
Download Resource Files
001 What is Convolution (part 1)
16:38
002 What is Convolution (part 2)
05:56
003 What is Convolution (part 3)
06:41
004 Convolution on Color Images
15:58
005 CNN Architecture
20:58
006 CNN Code Preparation
15:13
007 CNN for Fashion MNIST
06:46
008 CNN for CIFAR-10
04:28
009 Data Augmentation
08:51
010 Batch Normalization
05:14
011 Improving CIFAR-10 Results_part1
05:11
011 Improving CIFAR-10 Results_part2
05:11
06 – VGG and Transfer Learning
0/11
Download Resource Files
001 VGG Section Intro
03:04
002 What’s so special about VGG
07:00
003 Transfer Learning
08:22
004 Relationship to Greedy Layer-Wise Pretraining
02:19
005 Getting the data
02:17
006 Code pt 1_part1
04:41
006 Code pt 1_part2
04:41
007 Code pt 2
03:41
008 Code pt 3
03:27
009 VGG Section Summary
01:47
07 – ResNet (and Inception)
0/12
Download Resource Files
001 ResNet Section Intro
02:49
002 ResNet Architecture
12:45
003 Transfer Learning with ResNet in Code_part1
04:16
003 Transfer Learning with ResNet in Code_part2
04:16
004 Blood Cell Images Dataset
03:02
005 How to Build ResNet in Code_part1
05:38
005 How to Build ResNet in Code_part2
05:38
006 1×1 Convolutions
04:03
007 Optional Inception
06:47
008 Different sized images using the same network
04:12
009 ResNet Section Summary
02:27
08 – Object Detection (SSD RetinaNet)
0/14
Download Resource Files
001 SSD Section Intro
05:04
002 Object Localization
06:36
003 What is Object Detection
02:53
004 How would you find an object in an image
08:40
005 The Problem of Scale
03:47
006 The Problem of Shape
03:52
007 SSD Tensorflow Object Detection API (pt 1)
12:05
008 SSD Tensorflow Object Detection API (pt 2)_part1
06:07
008 SSD Tensorflow Object Detection API (pt 2)_part2
06:07
009 SSD for Video Object Detection_part1
05:59
009 SSD for Video Object Detection_part2
05:59
010 Optional Intersection over Union & Non-max Suppression
05:07
011 SSD Section Summary
02:52
09 – Neural Style Transfer
0/8
Download Resource Files
001 Style Transfer Section Intro
02:53
002 Style Transfer Theory
11:23
003 Optimizing the Loss
08:02
004 Code pt 1
07:46
005 Code pt 2
07:13
006 Code pt 3
03:50
007 Style Transfer Section Summary
02:22
10 – Class Activation Maps
0/4
Download Resource Files
001 Class Activation Maps (Theory)
07:09
002 Class Activation Maps (Code)_part1
04:57
002 Class Activation Maps (Code)_part2
04:57
11 – GANs (Generative Adversarial Networks)
0/3
Download Resource Files
001 GAN Theory
15:51
002 GAN Code
12:10
12 – Object Localization Project
0/16
Download Resource Files
001 Localization Introduction and Outline
13:38
002 Localization Code Outline (pt 1)
10:39
003 Localization Code (pt 1)
09:10
004 Localization Code Outline (pt 2)
04:52
005 Localization Code (pt 2)
11:03
006 Localization Code Outline (pt 3)
03:19
007 Localization Code (pt 3)
04:16
008 Localization Code Outline (pt 4)
03:19
009 Localization Code (pt 4)
02:06
010 Localization Code Outline (pt 5)
07:43
011 Localization Code (pt 5)
08:39
012 Localization Code Outline (pt 6)
07:06
013 Localization Code (pt 6)
07:37
014 Localization Code Outline (pt 7)
04:58
015 Localization Code (pt 7)
12:07
13 – Keras and Tensorflow 2 Basics Review
0/7
Download Resource Files
001 (Review) Tensorflow Basics
07:27
002 (Review) Tensorflow Neural Network in Code
09:43
003 (Review) Keras Discussion
06:48
004 (Review) Keras Neural Network in Code
06:37
005 (Review) Keras Functional API
04:26
006 (Review) How to easily convert Keras into Tensorflow 2.0 code
01:49
14 – Course Conclusion
0/2
Download Resource Files
001 What to Learn Next
03:00
15 – Setting Up Your Environment (FAQ by Student Request)
0/8
Download Resource Files
001 Pre-Installation Check
04:12
002 Anaconda Environment Setup_part1
06:46
002 Anaconda Environment Setup_part2
06:46
002 Anaconda Environment Setup_part3
06:46
003 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow_part1
08:45
003 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow_part2_part1
04:22
003 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow_part2_part2
04:22
16 – Extra Help With Python Coding for Beginners (FAQ by Student Request)
0/7
Download Resource Files
001 How to Code by Yourself (part 1)
15:54
002 How to Code by Yourself (part 2)
09:23
003 Proof that using Jupyter Notebook is the same as not using it_part1
06:14
003 Proof that using Jupyter Notebook is the same as not using it_part2
06:14
004 Python 2 vs Python 3
04:38
005 How to use Github & Extra Coding Tips (Optional)
11:12
17 – Effective Learning Strategies for Machine Learning (FAQ by Student Request)
0/7
Download Resource Files
001 How to Succeed in this Course (Long Version)
10:24
002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced
22:04
003 Machine Learning and AI Prerequisite Roadmap (pt 1)_part1
05:39
003 Machine Learning and AI Prerequisite Roadmap (pt 1)_part2
05:39
004 Machine Learning and AI Prerequisite Roadmap (pt 2)_part1
08:03
004 Machine Learning and AI Prerequisite Roadmap (pt 2)_part2
08:03
18 – Appendix FAQ Finale
0/3
Download Resource Files
001 What is the Appendix
02:48
002 BONUS
05:48
Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)
About Lesson

Please follow the instructions at the following link to add subtitles 

[ Các bạn làm theo chỉ dẫn ở link sau để thêm phụ đề cho bài giảng]

https://freestudy247.com/set-up-subtitle-for-video/

Join the conversation
Previous
Next

Please contact me via telegram

DMCA.com Protection Status