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Introduction
What is Deep Learning
Introduction to Neural Networks
How do Neural Networks LEARN?
Core terminologies used in Deep Learning
Activation Functions
Loss Functions
Optimizers
Parameters vs Hyperparameters
Epochs, Batches & Iterations
Conclusion to Terminologies
Introduction to Learning
Unsupervised Learning
Reinforcement Learning
Regularization
Introduction to Neural Network Architectures
Fully-Connected Feedforward Neural Nets
Recurrent Neural Nets
Convolutional Neural Nets
Introduction to the 5 Steps to EVERY Deep Learning Model
1. Gathering Data
2. Preprocessing the Data
3. Training your Model
4. Evaluating your Model
Conclusion to the Course
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