Hands on machine learning scikit learn von géron aurélien (27 Ergebnisse)

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Zustand: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. pp. 856.

paperback. Zustand: Sehr gut. Seiten; 9781491962299.2 Gewicht in Gramm: 2.

Zustand: New. In English.

Zustand: New.

Zustand: New. 2022. 3rd ed. Paperback. . . . . . Books ship from the US and Ireland.

Zustand: New. Idioma/Language: Inglés. The potential of machine learning today is extraordinary, yet many aspiring developers and tech professionals find themselves daunted by its complexity. Perhaps you're ready to jump in, but you're unsure where or how to begin. Whether you're looking to enhance your skill set and apply machine learning to real-world projects or are simply curious about how AI systems function, this book is your jumping-off place. In a way that's approachable yet deeply informative, author Aurà lien Gà ron delivers the ultimate introductory guide to machine learning and deep learning. With a focus on clear explanations and real-world Python examples, the book takes you through cutting-edge tools like scikit-learn and PyTorch--from basic regression techniques to advanced neural networks like transformers and generative adversarial networks. Whether you're a student, professional, or hobbyist, you'll gain the skills to begin building intelligent systems. Understand ML basics, including concepts like overfitting and hyperparameter tuning Learn to build end-to-end ML projects using scikit-learn, from data exploration to model evaluation Explore advanced architectures like convolutional and recurrent neural networks with PyTorch Discover techniques for unsupervised learning, such as clustering and anomaly detection Increase your expertise in state-of-the-art AI systems by fine-tuning pretrained models Build tangible skills with complete hands-on coding exercises and real-world applications *** Nota: Los envíos a España peninsular, Baleares y Canarias se realizan a través de mensajería urgente. No aceptamos pedidos con destino a Ceuta y Melilla.…

Paperback. Zustand: Brand New. 3rd edition. 850 pages. 9.19x7.00x1.71 inches. In Stock.

Zustand: New.

Taschenbuch. Zustand: Neu. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow | Concepts, Tools, and Techniques to Build Intelligent Systems | Aurélien Géron | Taschenbuch | Kartoniert / Broschiert | Englisch | 2022 | O'Reilly Media | EAN 9781098125974 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.…

Zustand: Akzeptabel. Zustand: Akzeptabel | Seiten: 834 | Sprache: Englisch | Produktart: Bücher | This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.…

Taschenbuch. Zustand: Neu. Neuware -Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. - Use Scikit-learn to track an example ML project end to end - Explore several models, including support vector machines, decision trees, random forests, and ensemble methods - Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection - Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers - Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learningLibri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch. …

Taschenbuch. Zustand: Neu. Hands-On Machine Learning with Scikit-Learn and PyTorch | Concepts, Tools, and Techniques to Build Intelligent Systems | Aurélien Géron | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | O'Reilly Media | EAN 9798341607989 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. Neuware - Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. - Use Scikit-learn to track an example ML project end to end - Explore several models, including support vector machines, decision trees, random forests, and ensemble methods - Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection - Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers - Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning. …

Taschenbuch. Zustand: Neu. Neuware - The potential of machine learning today is extraordinary, yet many aspiring developers and tech professionals find themselves daunted by its complexity. Whether you're looking to enhance your skill set and apply machine learning to real-world projects or are simply curious about how AI systems function, this book is your jumping-off place. With an approachable yet deeply informative style, author Aurélien Géron delivers the ultimate introductory guide to machine learning and deep learning. Drawing on the Hugging Face ecosystem, with a focus on clear explanations and real-world examples, the book takes you through cutting-edge tools like Scikit-Learn and PyTorch--from basic regression techniques to advanced neural networks. Whether you're a student, professional, or hobbyist, you'll gain the skills to build intelligent systems. - Understand ML basics, including concepts like overfitting and hyperparameter tuning - Complete an end-to-end ML project using scikit-Learn, covering everything from data exploration to model evaluation - Learn techniques for unsupervised learning, such as clustering and anomaly detection - Build advanced architectures like transformers and diffusion models with PyTorch - Harness the power of pretrained models--including LLMs--and learn to fine-tune them - Train autonomous agents using reinforcement learning.…

Softcover. Zustand: gut. 2022. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow In englischer Sprache. pages.

Taschenbuch. Zustand: Neu. Neuware -Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. - Use Scikit-learn to track an example ML project end to end - Explore several models, including support vector machines, decision trees, random forests, and ensemble methods - Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection - Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers - Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning Englisch. …

Softcover. Zustand: gut. 2019. Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, To In englischer Sprache. pages.