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Deep Learning: Convolutional Neural Networks in Python
Welcome
Introduction and Outline (2:42)
Special Offer! Get the VIP version of this course (1:14)
Where to get the code (8:26)
How to Succeed in this Course (5:51)
Google Colab
Intro to Google Colab, how to use a GPU or TPU for free (12:32)
Uploading your own data to Google Colab (11:41)
Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn? (8:54)
Machine Learning and Neurons
Review Section Introduction (2:37)
What is Machine Learning? (14:26)
Code Preparation (Classification Theory) (15:59)
Classification Notebook (8:40)
Code Preparation (Regression Theory) (7:18)
Regression Notebook (10:34)
The Neuron (9:58)
How does a model 'learn'? (10:53)
Making Predictions (6:45)
Saving and Loading a Model (4:27)
Suggestion Box (3:03)
Feedforward Artificial Neural Networks
Artificial Neural Networks Section Introduction (6:00)
Forward Propagation (9:40)
The Geometrical Picture (9:43)
Activation Functions (17:18)
Multiclass Classification (8:41)
How to Represent Images (12:36)
Code Preparation (ANN) (12:42)
ANN for Image Classification (8:36)
ANN for Regression (11:05)
Convolutional Neural Networks
What is Convolution? (part 1) (16:38)
What is Convolution? (part 2) (5:56)
What is Convolution? (part 3) (6:41)
Convolution on Color Images (15:58)
CNN Architecture (20:58)
CNN Code Preparation (15:13)
CNN for Fashion MNIST (6:46)
CNN for CIFAR-10 (4:28)
Data Augmentation (8:51)
Batch Normalization (5:14)
Improving CIFAR-10 Results (10:22)
Natural Language Processing (NLP)
Embeddings (13:12)
Code Preparation (NLP) (13:17)
Text Preprocessing (5:30)
CNNs for Text (8:07)
Text Classification with CNNs (6:10)
Appendix
What order should I take your courses in? (pt 1) (11:18)
What order should I take your courses in? (pt 2) (16:07)
How to Code by Yourself (part 1) (15:54)
How to Code by Yourself (part 2) (9:23)
How to Succeed in this Course (Long Version) (10:24)
BONUS: Where to get discount coupons and FREE deep learning material (5:31)
Extras
Link to Colab Notebooks
CNN for Fashion MNIST
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