Machine Learning Engineering: http://
amzn.to/2R9OEdT by @burkov ++
This is the perfect companion to his Hundred-Page Machine Learning Book: http://
amzn.to/3bFhtbF
————————
#ML #DataScience #AI #DataScientist
@kirkdborne
-
Machine Learning Engineering Complements Practical Machine Learning Study
By
–
-
Hands-On Language Models Book Uses PyTorch
By
–
The Hundred-Page Language Models Book — Hands-on with PyTorch: http://
amzn.to/4sJl7YC by @burkov -
Study Guide Covers Transformers and Large Language Models
By
–
Super Study Guide: Transformers & Large Language Models: http://
amzn.to/3SW6YYm by @afshinea & @shervinea Beautifully presented, excellent content, timely, thorough, educational #LLMs #MachineLearning #AI #GenAI #DataScience #DataScientist #GenerativeAI -
Deep Learning With C++ Covers CUDA-Based Neural Network Deployment
By
–
Deep Learning with C++ — Design and deploy neural networks using CUDA for high-performance AI in C++ Get the book at http://
amzn.to/4nzdKB4 from @PacktPublishing @PacktDataML -
Guide Combines Neo4j Knowledge Graphs and LLMs for Intelligent Search
By
–
Available at http://
amzn.to/4l9lLKO This LLM book is for database developers and data scientists who want to leverage knowledge graphs with Neo4j and its vector search capabilities to build intelligent search and recommendation systems. Working knowledge of Python and Java is -
Linear Algebra Links Signal Processing and Machine Learning
By
–
Signal Processing is a surprisingly powerful domain at the intersection of real world applications (interesting data) and theory (interesting math). Linear Algebra for Data Science, Machine Learning, and Signal Processing: http://
amzn.to/3Rc73JB Signal Processing — A -
Learning Pattern-Finding Algorithms Helps Explain AI-Driven Business Decisions
By
–
I always recommend to start with learning how different algorithms find patterns in data that signal, inform, and fuel business value and operational decisions. AI is basically the automated version of those data-fueled algorithms, decisions, and operations. See this book…
-
Kaggle Book Covers Machine Learning, Generative AI, and Competitions
By
–
The Kaggle Book — Master Data Analysis and Data Science Competitions with Machine Learning, GenAI, and LLMs [2nd Ed.]: http://
amzn.to/4pxJpTC v/ @PacktDataML Table of Contents:
Introducing Data Science Competition
Organizing Data with Datasets
Work & Learn with Kaggle -
Python Guide Teaches Supervised, Unsupervised, and Deep Learning
By
–
Check this out… AI Programming with Python — From Zero to Hero: http://
amzn.to/43TkNea Thorough introductions to AI, Machine Learning, and Deep Learning Hands-on introductions to Python Discussions of supervised and unsupervised learning Explorations of -
Domain-Specific Small Language Models Target Efficient Local Deployment
By
–
"Domain-Specific Small Language Models: Efficient AI for local deployment" Available at http://
amzn.to/4g7mVqW via @ManningBooks