https://magnus919.com/tags/rag/Recent content in RAG on Notes from the Rabbit HoleHugoen© [Magnus Hedemark](https://github.com/magnus919)Mon, 06 Jan 2025 00:00:00 +0000https://magnus919.com/notes/humble-book-bundles/machine-learning-engineer-masterclass/Mon, 06 Jan 2025 00:00:00 +0000https://magnus919.com/notes/humble-book-bundles/machine-learning-engineer-masterclass/<h2 id="about-the-bundle">About the Bundle</h2> <p>This bundle includes the following books:</p> <ul> <li><a href="#Machine-Learning-Engineering-with-Python">Machine Learning Engineering with Python</a> by Andrew P. McMahon</li> <li><a href="##-Building-LLM-Powered-Applications"># Building LLM Powered Applications</a> by Valentina Alto</li> <li><a href="#XGBoost-for-Regression-Predictive-Modeling-and-Time-Series-Analysis">XGBoost for Regression Predictive Modeling and Time Series Analysis</a> by Partha Pritam Deka, Joyce Weiner</li> <li><a href="#Mastering-NLP-from-Foundations-to-LLMs">Mastering NLP from Foundations to LLMs</a> by Gazit, Meysam Ghaffari</li> <li><a href="#Mastering-PyTorch">Mastering PyTorch</a> by Ashish Ranjan Jha</li> <li><a href="#Python-Feature-Engineering-Cookbook">Python Feature Engineering Cookbook</a> by Soledad Galli</li> <li><a href="#Hands-On-Genetic-Algorithms-with-Python">Hands-On Genetic Algorithms with Python</a> by Eyal Wirsansky</li> <li><a href="#The-Machine-Learning-Solutions-Architect-Handbook">The Machine Learning Solutions Architect Handbook</a> by David Ping</li> <li><a href="#Causal-Inference-and-Discovery-in-Python">Causal Inference and Discovery in Python</a> by Aleksander Molak</li> <li><a href="#TinyML-Cookbook">TinyML Cookbook</a> by Gian Marco Iodice</li> <li><a href="#RAG-Driven-Generative-AI">RAG-Driven Generative AI</a> by Denis Rothman</li> <li><a href="#15-Math-Concepts-Every-Data-Scientist-Should-Know">15 Math Concepts Every Data Scientist Should Know</a> by David Hoyle</li> <li><a href="#Machine-Learning-with-PyTorch-and-Scikit-Learn">Machine Learning with PyTorch and Scikit-Learn</a> by Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili</li> <li><a href="#Machine-Learning-with-R">Machine Learning with R</a> by Brett Lantz</li> <li><a href="#Bayesian-Analysis-with-Python">Bayesian Analysis with Python</a> by Martin</li> <li><a href="#Causal-Inference-in-R">Causal Inference in R</a> by Subhajit Das</li> <li><a href="#Artificial-Intelligence-for-Cybersecurity">Artificial Intelligence for Cybersecurity</a> by Bojan Kolosnjaji, Huang Xiao, Peng Xu, Apostolis Zarras</li> <li><a href="#Modern-Time-Series-Forecasting-with-Python">Modern Time Series Forecasting with Python</a> by Manu Joseph, Jeffrey Tackes</li> <li><a href="#Python-Machine-Learning-By-Example">Python Machine Learning By Example</a> by Yuxi (Hayden) Liu</li> <li><a href="#LLM-Engineer%27s-Handbook">LLM Engineer&rsquo;s Handbook</a> by Paul Iusztin, Maxime Labonne</li> <li><a href="#Deep-Reinforcement-Learning-Hands-On">Deep Reinforcement Learning Hands-On</a> by Maxim Lapan</li> </ul>