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- Introduction
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Classroom Contents
Deep Learning Full Course - Complete Deep Learning for Beginners
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- 1 - Introduction
- 2 - Installing Python and other IDEs
- 3 - Variables in Python
- 4 - Data Types in Python
- 5 - Operators in Python
- 6 - Python Strings
- 7 - Data Structures in Python
- 8 - Flow Control Statements in Python
- 9 - Python Functions
- 10 - Object-Oriented Programming in Python
- 11 - Numpy in Python
- 12 - Pandas in Python
- 13 - Matplotlib in Python
- 14 - History behind Deep Neural Networks
- 15 - Relationship between Artificial and Biological Neuron
- 16 - Working of Perceptron
- 17 - Demo on McCullohPitt and Rosenblat Neurons
- 18 - Architecture of Artificial Neural Network
- 19 - Activation Functions
- 20 - Demo on Wine Dataset using Keras Sequential Model
- 21 - Back-propagation and Gradient Descent Algorithm
- 22 - Demo on MNIST dataset
