Study

Data Structures and Algorithms

Textbook

PyTorch Pocket Reference

A book by Chip Huyen

An Introduction to Statistical Learning

The Elements of Statistical Learning

System Design Notes

Approximately 150 pages of ChatGPT-generated study notes drawing on multiple sources, including Designing Data-Intensive Applications.

Deep Learning Specialization

Deep learning foundations, neural networks, convolutional networks, and sequence models.

Machine Learning Engineering for Production (MLOps)

Designing, deploying, and maintaining machine learning systems in production.

CMU 11-768: AI Agents

Study of AI agents using course materials from Carnegie Mellon University.

Understanding Machine Learning: From Theory to Algorithms

By Shai Shalev-Shwartz and Shai Ben-David.

Mathematical foundations of machine learning and learning algorithms.

Pattern Recognition and Machine Learning

By Christopher Bishop.

Probabilistic methods for pattern recognition and machine learning.

Deep Learning

By Ian Goodfellow, Yoshua Bengio, and Aaron Courville.

Foundations and methods of deep learning and neural networks.

CMU 10-617: Intermediate Deep Learning

Study of course materials from Carnegie Mellon University.

CMU 10-707: Deep Learning

Study of course materials from Carnegie Mellon University.

CMU 10-708: Probabilistic Graphical Models

Study of course materials from Carnegie Mellon University.

CMU 10-715: Advanced Introduction to Machine Learning

Study of course materials from Carnegie Mellon University.

CMU 10-725: Convex Optimization

Study of course materials from Carnegie Mellon University.

CMU 16-720: Computer Vision

Study of course materials from Carnegie Mellon University.

CMU 11-711: Advanced NLP

Study of advanced natural language processing using course materials from Carnegie Mellon University.