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Introduction to Artificial Intelligence with Python
Chapters

1Orientation and Python Environment Setup

2Python Essentials for AI

3AI Foundations and Problem Framing

4Math for Machine Learning

5Data Handling with NumPy and Pandas

6Data Cleaning and Feature Engineering

7Supervised Learning Fundamentals

8Model Evaluation and Validation

9Unsupervised Learning Techniques

10Optimization and Regularization

11Neural Networks with PyTorch

Tensors and AutogradComputational GraphsBuilding ModulesForward and BackwardActivation FunctionsInitialization in PyTorchOptimizers in PyTorchDataloaders and DatasetsTraining LoopsGPU AccelerationSaving and LoadingDebugging TipsMixed PrecisionRegularization in NNReproducibility in PyTorch

12Deep Learning Architectures

13Computer Vision Basics

14Model Deployment and MLOps

Courses/Introduction to Artificial Intelligence with Python/Neural Networks with PyTorch

Neural Networks with PyTorch

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Build, train, and debug neural networks in PyTorch using modern training utilities.

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GPU Acceleration

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