Books / AI and ML / MLOps

AI and ML

All Programming languages 1873AI and ML 893Software Development 611Algorithms and theory 548WEB development 472DevOps and Infrastructure 363Other 269Cybersecurity 233OS and System 214Game development 187Databases 157Embedded systems 153IT management 110
All Data Science 307Machine learning 170LLM 129Neural networks 97Computer Vision 41ChatGPT 39TensorFlow 30PyTorch 23Natural Language Processing 21MLOps 19熊猫 9AI Agents 1
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Machine Learning Upgrade: A Guide to MLOps, LLMs, and ML Infrastructure for Data Scientists

Machine Learning Upgrade: A Guide to MLOps, LLMs, and ML Infrastructure for Data Scientists

A

Kristen Kerrer, Caleb Kaiser

AI and ML
EN
Learning AutoML: Automating ML Pipelines with AutoGluon, Leading Frameworks, and Real-World Integration

Learning AutoML: Automating ML Pipelines with AutoGluon, Leading Frameworks, and Real-World Integration

A

Kerem Tomak

AI and ML
EN
Machine Learning Platform Engineering: Build an internal developer platform for ML and AI systems

Machine Learning Platform Engineering: Build an internal developer platform for ML and AI systems

A

Benjamin Tan Wei Hao, Shanoop Padmanabhan, Varun Mallya

AI and ML

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A Excellent — copyable text, TOC, metadata B Good — text present, some data missing C Average — text is partially extractable D Poor — most likely a scan F Scan without OCR — text cannot be extracted