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Building Machine Learning Systems with Python - Third Edition
Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow
Taschenbuch von Luis Pedro Coelho (u. a.)
Sprache: Englisch

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Beschreibung
Build intelligent end-to-end machine learning systems with Python
Key FeaturesUse scikit-learn and TensorFlow to train your machine learning models
Implement popular supervised and unsupervised machine learning algorithms in Python
Discover best practices for building production-grade machine learning systems from scratch

Book Description
Machine learning enables systems to make predictions based on historical data. Python is one of the most popular languages used to develop machine learning applications, thanks to its extensive library support. This updated third edition of Building Machine Learning Systems with Python helps you get up to speed with the latest trends in artificial intelligence (AI).

With this guide's hands-on approach, you'll learn to build state-of-the-art machine learning models from scratch. Complete with ready-to-implement code and real-world examples, the book starts by introducing the Python ecosystem for machine learning. You'll then learn best practices for preparing data for analysis and later gain insights into implementing supervised and unsupervised machine learning techniques such as classification, regression and clustering. As you progress, you'll understand how to use Python's scikit-learn and TensorFlow libraries to build production-ready and end-to-end machine learning system models, and then fine-tune them for high performance.

By the end of this book, you'll have the skills you need to confidently train and deploy enterprise-grade machine learning models in Python.

What you will learnBuild a classification system that can be applied to text, images, and sound
Solve regression-related problems using scikit-learn and TensorFlow
Recommend products to users based on their previous purchases
Explore different methods of applying deep neural networks to your data
Understand recent advances in computer vision and natural language processing (NLP)
Deploy Amazon Web Services (AWS) to run data models on the cloud

Who this book is for:
¿This book is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. Prior knowledge of Python programming is expected.
Build intelligent end-to-end machine learning systems with Python
Key FeaturesUse scikit-learn and TensorFlow to train your machine learning models
Implement popular supervised and unsupervised machine learning algorithms in Python
Discover best practices for building production-grade machine learning systems from scratch

Book Description
Machine learning enables systems to make predictions based on historical data. Python is one of the most popular languages used to develop machine learning applications, thanks to its extensive library support. This updated third edition of Building Machine Learning Systems with Python helps you get up to speed with the latest trends in artificial intelligence (AI).

With this guide's hands-on approach, you'll learn to build state-of-the-art machine learning models from scratch. Complete with ready-to-implement code and real-world examples, the book starts by introducing the Python ecosystem for machine learning. You'll then learn best practices for preparing data for analysis and later gain insights into implementing supervised and unsupervised machine learning techniques such as classification, regression and clustering. As you progress, you'll understand how to use Python's scikit-learn and TensorFlow libraries to build production-ready and end-to-end machine learning system models, and then fine-tune them for high performance.

By the end of this book, you'll have the skills you need to confidently train and deploy enterprise-grade machine learning models in Python.

What you will learnBuild a classification system that can be applied to text, images, and sound
Solve regression-related problems using scikit-learn and TensorFlow
Recommend products to users based on their previous purchases
Explore different methods of applying deep neural networks to your data
Understand recent advances in computer vision and natural language processing (NLP)
Deploy Amazon Web Services (AWS) to run data models on the cloud

Who this book is for:
¿This book is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. Prior knowledge of Python programming is expected.
Über den Autor
Luis Pedro Coelho is a computational biologist who analyzes DNA from microbial communities to characterize their behavior. He has also worked extensively in bioimage informatics - the application of machine learning techniques for the analysis of images of biological specimens. His main focus is on the processing and integration of large-scale datasets. He has a PhD from Carnegie Mellon University and has authored several scientific publications. In 2004, he began developing in Python and has contributed to several open source libraries. He is currently a faculty member at Fudan University in Shanghai.
Details
Erscheinungsjahr: 2018
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 406
ISBN-13: 9781788623223
ISBN-10: 1788623223
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Pedro Coelho, Luis
Richert, Willi
Brucher, Matthieu
Auflage: Third
Hersteller: Packt Publishing
Maße: 235 x 191 x 22 mm
Von/Mit: Luis Pedro Coelho (u. a.)
Erscheinungsdatum: 26.07.2018
Gewicht: 0,755 kg
preigu-id: 120693454
Über den Autor
Luis Pedro Coelho is a computational biologist who analyzes DNA from microbial communities to characterize their behavior. He has also worked extensively in bioimage informatics - the application of machine learning techniques for the analysis of images of biological specimens. His main focus is on the processing and integration of large-scale datasets. He has a PhD from Carnegie Mellon University and has authored several scientific publications. In 2004, he began developing in Python and has contributed to several open source libraries. He is currently a faculty member at Fudan University in Shanghai.
Details
Erscheinungsjahr: 2018
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 406
ISBN-13: 9781788623223
ISBN-10: 1788623223
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Pedro Coelho, Luis
Richert, Willi
Brucher, Matthieu
Auflage: Third
Hersteller: Packt Publishing
Maße: 235 x 191 x 22 mm
Von/Mit: Luis Pedro Coelho (u. a.)
Erscheinungsdatum: 26.07.2018
Gewicht: 0,755 kg
preigu-id: 120693454
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