Machine Learning On Private Data – alle Bücher, LPs und CDs, Seite 4

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Omar Sanseviero, Pedro Cuenca, Apolinario Passos, Jonathan Whitaker
Hands-On Generative AI with Transformers and Diffusion Models

Learn to use generative AI techniques to create novel text, images, audio, and even music with this practical, hands-on book. Readers will understand how state-of-the-art generative models work, how to fi…

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Chad Sanderson, Mark Freeman, B E Schmidt
Data Contracts

Poor data quality can cause major problems for data teams, from breaking revenue-generating data pipelines to losing the trust of data consumers. Despite the importance of data quality, many data teams st…

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Bing Zhang
Machine Learning-Based Hyperspectral Image Processing

An authoritative deep dive into the most recent machine learning approaches to hyperspectral remote sensing image processingIn Machine Learning-Based Hyperspectral Image Processing, distinguished research…

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Keita Broadwater, Namid Stillman
Graph Neural Networks in Action

About the bookIn Graph Neural Networks in Action you will create deep learning models that are perfect for working with interconnected graph data. Start with a comprehensive introduction to graph data's u…

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Mariano Mattei
Data-Driven Cybersecurity

Measure, improve, and communicate the value of your security program.Every business decision should be driven by data---and cyber security is no exception. In Data-Driven Cybersecurity , you'll master the…

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Ryan Day
Hands-On APIs for AI and Data Science

Are you ready to grow your skills in AI and data science? A great place to start is learning to build and use APIs in real-world data and AI projects. API skills have become essential for AI and data scie…

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Constantin Gonciulea, Charlee Stefanski
Building Quantum Software in Python

A developer-centric look at quantum computing.The demand for developers who can implement solutions with quantum resources is growing larger every day. Building Quantum Software with Python gives you the …

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Edward Dongbo Cui
Vectorization

Enables readers to develop foundational and advanced vectorization skills for scalable data science and machine learning and address real-world problemsOffering insights across various domains such as com…

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Pam Baker
Agentic AI for Dummies

An easy-to-follow guide to demystifying Agentic AI, the next step in the evolution of artificial intelligenceAgentic AI is the next big leap in artificial intelligence. Agentic systems don't just respond …

lieferbar ab 27.1.2026.

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Luca Massaron
Machine Learning for Dummies

The most human-friendly book on machine learningSomewhere buried in all the systems that drive artificial intelligence, you'll find machine learning-the process that allows technology to build knowledge b…

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Navnit Shukla, Kien Pham, Srikanth Sopirala, Harsha Tadiparthi
Ai-Ready Data Blueprints

Companies innovating with generative AI understand that having the right data foundation is critical for success and profitability. To best position themselves for long-term success, organizations must pr…

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Luca Antiga, Eli Stevens, Howard Huang, Thomas Viehmann
Deep Learning with Pytorch, Second Edition

Everything you need to create neural networks with PyTorch, including Large Language and diffusion models.Deep Learning with PyTorch, Second Edition updates the bestselling original guide with new insight…

lieferbar ab 27.1.2026.

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Agricultural Insights from Space

Agricultural Insights from Space offers a comprehensive exploration of how geospatial technology and machine learning are transforming modern agriculture. From satellite data acquisition and soil mapping …

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Wei-Meng Lee
Hugging Face in Action

Everything you need to know about using the tools, libraries, and models at Hugging Face---from transformers, to RAG, LangChain, and Gradio.Hugging Face is the ultimate resource for machine learning engin…

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Robert Osazuwa Ness
Causal AI

From the back cover:Causal AI teaches you how to build machine learning and deep learning models that implement causal reasoning. Discover why leading AI engineers are so excited by causal reasoning, and …

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Tiny Machine Learning: Design Principles and Applications

An expert compilation of on-device training techniques, regulatory frameworks, and ethical considerations of TinyML design and developmentIn Tiny Machine Learning: Design Principles and Applications, a te…

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Guglielmo Iozzia
Domain-Specific Small Language Models

Bigger isn't always better. Train and tune highly focused language models optimized for domain specific tasks.When you need a language model to respond accurately and quickly about a specific field of kno…

lieferbar ab 17.3.2026.

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Mark Liu
Build a Text-To-Image Generator (from Scratch)

Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.This boo…

lieferbar ab 27.1.2026.

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Ahmed Menshawy, Sameh Mohamed, Maraim Rizk Masoud
Scaling Graph Learning for the Enterprise

Tackle the core challenges related to enterprise-ready graph representation and learning. With this hands-on guide, applied data scientists, machine learning engineers, and practitioners will learn how to…

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Daniel Costea
Building AI Agents in .Net

Build AI applications that integrate multiple models, data sources, and other components using Microsoft Agent Framework.Even simple AI applications need to combine LLMs and other models, functions and pl…

lieferbar ab 19.5.2026.

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