Introduction machine learning python von müller andreas (14 Ergebnisse)

Paperback. Zustand: Very Good. Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.…

Paperback. Zustand: Good. Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.…

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.

Paperback. Zustand: Very Good+. First Edition; Third Printing. 378 pages; minor creasing to back cover's bottom corner. Very Good condition otherwise. No other noteworthy defects. No markings. ; - Your satisfaction is our priority. We offer free returns and respond promptly to all inquiries. Your item will be carefully cushioned in bubble wrap and securely boxed. All orders ship on the same or next business day. Buy with confidence.…

Paperback. Zustand: Very Good+. First Edition; First Printing. 376 pages; Very Good condition. No noteworthy defects. No markings. ; - Your satisfaction is our priority. We offer free returns and respond promptly to all inquiries. Your item will be carefully cushioned in bubble wrap and securely boxed. All orders ship on the same or next business day. Buy with confidence.…

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. 400.

Zustand: New. In English.

paperback. Zustand: Gut. 400 Seiten; 9781449369415.3 Gewicht in Gramm: 1.

Zustand: New. Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical w.

Taschenbuch. Zustand: Neu. Neuware -Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:- Fundamental concepts and applications of machine learning- Advantages and shortcomings of widely used machine learning algorithms- How to represent data processed by machine learning, including which data aspects to focus on- Advanced methods for model evaluation and parameter tuning- The concept of pipelines for chaining models and encapsulating your workflow- Methods for working with text data, including text-specific processing techniques- Suggestions for improving your machine learning and data science skillsLibri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch.…

Taschenbuch. Zustand: Neu. Neuware - Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:- Fundamental concepts and applications of machine learning- Advantages and shortcomings of widely used machine learning algorithms- How to represent data processed by machine learning, including which data aspects to focus on- Advanced methods for model evaluation and parameter tuning- The concept of pipelines for chaining models and encapsulating your workflow- Methods for working with text data, including text-specific processing techniques- Suggestions for improving your machine learning and data science skills.…

Taschenbuch. Zustand: Neu. Neuware -Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:- Fundamental concepts and applications of machine learning- Advantages and shortcomings of widely used machine learning algorithms- How to represent data processed by machine learning, including which data aspects to focus on- Advanced methods for model evaluation and parameter tuning- The concept of pipelines for chaining models and encapsulating your workflow- Methods for working with text data, including text-specific processing techniques- Suggestions for improving your machine learning and data science skills Englisch.…