Packt Publishing Graph Machine Learning: Learn about the latest advancements in graph data to build robust machine learning models

Graph Machine Learning: Take graph data to the next level by applying machine learning techniques and algorithms

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Graph Algorithms for Data Science: With Examples in Neo4j

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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python

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LLMs in Enterprise: Design strategies, patterns, and best practices for large language model development

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Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines

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Granular Computing Based Machine Learning: A Big Data Processing Approach: 35 (Studies in Big Data, 35)

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Practical Discrete Mathematics: Discover math principles that fuel algorithms for computer science and machine learning with Python

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LLM Design Patterns: A Practical Guide to Building Robust and Efficient AI Systems

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Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, ... (Lecture Notes in Computer Science, 12976)

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Applied Generative AI for Beginners: Practical Knowledge on Diffusion Models, ChatGPT, and Other LLMs

Apress

Building AI Agents with LLMs, RAG, and Knowledge Graphs: A practical guide to autonomous and modern AI agents

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Intelligent Systems in Big Data, Semantic Web and Machine Learning: 1344 (Advances in Intelligent Systems and Computing, 1344)

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Learning Social Media Analytics with R: Transform data from social media platforms into actionable business insights

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Graph Representation Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning)

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Building AI Intensive Python Applications: Create intelligent apps with LLMs and vector databases

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Handbook of Computational Social Science - Vol 1 & Vol 2: 1-2 (European Association of Methodology Series)

Routledge

Mastering Java Machine Learning: A Java developer's guide to implementing machine learning and big data architectures

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Machine Learning and Artificial Intelligence: Concepts, Algorithms and Models

Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python

Wiley

Springer Graph-Based Modelling in Science, Tech and Art 107

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Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

Springer

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

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Adaptive Semantics Visualization: 646 (Studies in Computational Intelligence, 646)

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Machine Learning and Knowledge Discovery in Databases: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, ... in Computer and Information Science, 1168)

Springer