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Master PyTorch For Artificial Neural Networks (ANN) and Deep Learning
Introduction to the Course
Welcome to the Course (2:32)
Data and Code
Get Started With the Python Data Science Environment: Anaconda (10:57)
Anaconda for Mac Users (4:05)
The iPython Environment (19:13)
Why PyTorch? (9:42)
Install PyTorch (3:36)
Installing PyTorch-Written Instructions
Further Installation Instructions for Mac (1:19)
Working With CoLabs (7:13)
Non PyTorch Python Data Science Packages
Python Packages for Data Science (3:16)
Introduction to Numpy (3:46)
Create Numpy Arrays (10:51)
Numpy Operations (16:48)
Numpy for Basic Vector Arithmetric (6:16)
Numpy for Basic Matrix Arithmetic (6:32)
PyTorch Basics: What Is a Tensor? (2:36)
Explore PyTorch Tensors and Numpy Arrays (4:26)
Some Basic PyTorch Tensor Operations (3:40)
Other Python Data Science Packages For Dealing With Data
Read CSV (5:42)
Read Excel (5:31)
Basic Data Exploration With Pandas (11:20)
Basic Statistical Analysis With PyTorch
Ordinary Least Squares (OLS) Regression- Theory (10:44)
OLS Linear Regression-Without PyTorch (11:18)
OLS Linear Regression From First Principles-Theory (12:48)
OLS Linear Regression From First Principles-With PyTorch (4:33)
More OLS With PyTorch (11:23)
Generalised Linear Models (GLMs)-Theory (5:25)
Logistic Regression-Without PyTorch (5:06)
Logistic Regression-With PyTorch (4:52)
Introduction to Artificial Neural Networks (ANN)
Introduction to ANN (9:17)
PyTorch ANN Syntax (5:24)
What Are Activation Functions? Theory (5:50)
More on Backpropagation (10:20)
Bringing Them Together (14:46)
Setting Up ANN Analysis With PyTorch (6:21)
DNN Analysis with PyTorch (11:26)
More DNNs (8:43)
DNNs For Identifying Credit Card Fraud (9:40)
An Explanation of Accuracy Metrics (4:19)
Neural Networks on Images
What Are Images? (4:54)
Read in Images in Python (7:46)
Basic Image Conversions (3:07)
Why AI and Deep Learning? (9:51)
Artificial Neural Networks (ANN) For Image Classification (10:50)
Deep Neural Networks (DNN) For Image Classification (5:27)
Introduction to Artificial Intelligence (AI) and Deep Learning
What is CNN? (11:25)
Implement CNN on Imagery Data (7:33)
More on CNN (4:36)
Introduction to Transfer Learning: Theory (7:41)
Implement CNN Using a Pre-Trained Model (7:25)
Generalised Linear Models (GLMs)-Theory
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