What You will Learn?

• 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
• Supervised 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
• Gathering Data
• Preprocessing the Data
• Training your Model
• Evaluating your Model
• Optimizing your Model's Accuracy
• Conclusion to the Course