Explore foundational and essential topics in AI/ML with these curated notebooks. Each notebook is well-commented and documented to help you follow and understand the concepts with ease. These notebooks can be run directly in your browser, providing an interactive and hands-on learning experience.
Learn Python fundamentals for machine learning, including data structures and libraries.
Explore the basics of PyTorch, including tensors and operations.
Deep dive into tensors and learn about operations in PyTorch.
Understand activation functions and their role in deep learning models.
Learn linear regression and its implementation in PyTorch.
Explore how the forward and backward passes work in PyTorch.
Understand the foundational concepts of neural networks.
Learn how to train neural networks effectively using PyTorch.
Understand and implement logistic regression for classification tasks.