About the Bundle
This bundle includes the following books:
- Machine Learning Engineering with Python by Andrew P. McMahon
- # Building LLM Powered Applications by Valentina Alto
- XGBoost for Regression Predictive Modeling and Time Series Analysis by Partha Pritam Deka, Joyce Weiner
- Mastering NLP from Foundations to LLMs by Gazit, Meysam Ghaffari
- Mastering PyTorch by Ashish Ranjan Jha
- Python Feature Engineering Cookbook by Soledad Galli
- Hands-On Genetic Algorithms with Python by Eyal Wirsansky
- The Machine Learning Solutions Architect Handbook by David Ping
- Causal Inference and Discovery in Python by Aleksander Molak
- TinyML Cookbook by Gian Marco Iodice
- RAG-Driven Generative AI by Denis Rothman
- 15 Math Concepts Every Data Scientist Should Know by David Hoyle
- Machine Learning with PyTorch and Scikit-Learn by Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili
- Machine Learning with R by Brett Lantz
- Bayesian Analysis with Python by Martin
- Causal Inference in R by Subhajit Das
- Artificial Intelligence for Cybersecurity by Bojan Kolosnjaji, Huang Xiao, Peng Xu, Apostolis Zarras
- Modern Time Series Forecasting with Python by Manu Joseph, Jeffrey Tackes
- Python Machine Learning By Example by Yuxi (Hayden) Liu
- LLM Engineer’s Handbook by Paul Iusztin, Maxime Labonne
- Deep Reinforcement Learning Hands-On by Maxim Lapan