Foundations of Machine Learning
Introduction to AI
Basic Statistics
Linear Algebra Basics
Calculus Basics
Programming with Python
Deep Learning Concepts
Neural Networks Overview
Types of Neural Networks
Activation Functions
Loss Functions
Gradient Descent
Frameworks and Tools
TensorFlow Basics
Keras Introduction
PyTorch Basics
Jupyter Notebooks
Model Training and Evaluation
Data Preprocessing
Training Neural Networks
Model Evaluation Metrics
Overfitting and Regularization
Practical Applications
Image Classification
Natural Language Processing
Generative Models
Real-World Projects
Advanced Topics
Transfer Learning
Reinforcement Learning
Explainable AI
Deployment Strategies
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