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Tensorflow and Keras Masterclass For Machine Learning and AI in Python
Introduction to the Course
Tensorflow and Keras For Data Science (2:12)
Data and Code
Python Data Science Environment (10:57)
For Mac Users (4:05)
Install Tensorflow (15:12)
Written Instructions for Tensorflow Install
Install Keras on Windows 10 (5:16)
Install Keras with Mac (4:19)
Written Keras Installation Instructions
Introduction to Python Data Science Packages
Python Packages For Data Science (3:16)
Introduction to Numpy (3:46)
Create Numpy (10:51)
Numpy for Statistical Operations (7:23)
Introduction to Pandas (12:06)
Read in CSV (7:13)
Read in Excel (5:31)
Basic Data Cleaning (4:30)
Introduction to Tensorflow
A Brief Touchdown (2:36)
A Brief Touchdown: Computational Graphs (2:56)
Common Mathematical Operator
A Tensorflow Session (4:37)
Interactive Tensorflow Session (1:38)
Constants and Variables in Tensorflow (3:42)
Placeholders in Tensorflow (3:58)
Introduction to Keras
What is Keras? (3:29)
Some Preliminary Tensorflow and Keras Applications
Theory of Linear Regression (OLS) (10:44)
OLS From First Principles (9:22)
Visualize the Results of OLS (3:28)
Multiple Regression With Tensorflow-Part 1 (5:08)
Estimate With Tensorflow Estimators (3:05)
Multiple Regression With Tensorflow Estimators (5:24)
More on Linear Regressor Estimator (8:24)
GLM: Generalized Linear Model (5:25)
Linear Classifier For Binary Classification (9:33)
Accuracy Assessment For Binary Classification (4:19)
Linear Classification with Binary Classification With Mixed Predictors (8:15)
Softmax Classification With Tensorflow (7:35)
Some Basic Concepts
What is Machine Learning? (5:32)
Theory Behind ANN (Artificial Neural Network) and DNN (Deep Neural Networks) (9:17)
Unsupervised Learning With Tensorflow and Keras
What is Unsupervised Learning? (5:32)
Autoencoders for Unsupervised Classification (1:46)
Autoencoders in Tensorflow (Binary Class Problem) (7:32)
Autoencoders in Tensorflow (Multiple Classes) (5:43)
Autoencoders in Keras (Simple) (5:43)
Autoencoders in Keras (Sparsity Constraints) (4:32)
Neural Network for Tensorflow & Keras
Multi Layer Perceptron (MLP) with Tensorflow (6:24)
Multi Layer Perceptron (MLP) With Keras (3:31)
Keras MLP For Binary Classification (4:01)
Keras MLP for Multiclass Classification (6:01)
Keras MLP for Regression (3:27)
Deep Learning For Tensorflow & Keras
Deep Neural Network (DNN) Classifier With Tensorflow (6:47)
Deep Neural Network (DNN) Classifier With Mixed Predictors (8:11)
Deep Neural Network (DNN) Regression With Tensorflow (5:24)
Wide & Deep Learning (Tensorflow) (11:34)
DNN Classifier With Keras (3:30)
DNN Classifier With Keras-Example 2 (4:23)
Autoencoders with Convolution Neural Networks (CNN)
Autoencoders With CNN-Tensorflow (7:15)
Autoencoders With CNN- Keras (4:46)
Recurrent Neural Network (RNN)
Introduction to RNN (5:40)
LSTM for Time Series (6:24)
LSTM for Stock Prices (7:21)
GLM: Generalized Linear Model
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