Many Python developers are curious about what machine learning is and how it can be concretely applied to solve issues faced in businesses handling medium to large amount of data. Machine Learning with Python teaches you the basics of machine learning and provides a thorough hands-on understanding of the subject.
You’ll learn important machine learning concepts and algorithms, when to use them, and how to use them. The book will cover a machine learning workflow: data preprocessing and working with data, training algorithms, evaluating results, and implementing those algorithms into a production-level system.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
An Introduction
L'autore:Andreas Müller received his PhD in machine learning from the University of Bonn. After working as a machine learning researcher on computer vision applications at Amazon for a year, he recently joined the Center for Data Science at the New York University. In the last four years, he has been maintainer and one of the core contributor of scikit-learn, a machine learning toolkit widely used in industry and academia, and author and contributor to several other widely used machine learning packages. His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science and democratize the access to high-quality machine learning algorithms.
Sarah is a data scientist who has spent a lot of time working in start-ups. She loves Python, machine learning, large quantities of data, and the tech world. She is an accomplished conference speaker, currently resides in New York City, and attended the University of Michigan for grad school.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Spese di spedizione:
GRATIS
In U.S.A.
Descrizione libro Oand#8242;Reilly, 2016. PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo WO-9781449369415
Descrizione libro O'Reilly Media, Inc, USA, United States, 2016. Paperback. Condizione: New. Language: English. Brand new Book. 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 Muller 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. Codice articolo BTA9781449369415
Descrizione libro O'Reilly Media, Inc, USA, United States, 2016. Paperback. Condizione: New. Language: English. Brand new Book. 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 Muller 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. Codice articolo AAH9781449369415
Descrizione libro O'Reilly Media 2016-10-07, Beijing, 2016. paperback. Condizione: New. Language: ENG. Codice articolo 9781449369415
Descrizione libro O'Reilly Media 10/20/2016, 2016. Paperback or Softback. Condizione: New. Introduction to Machine Learning with Python: A Guide for Data Scientists. Book. Codice articolo BBS-9781449369415
Descrizione libro O'Reilly Media, 2016. Paperback. Condizione: new. Codice articolo 9781449369415
Descrizione libro Oand#8242;Reilly. Condizione: new. Book is in NEW condition. Satisfaction Guaranteed! Fast Customer Service!!. Codice articolo MBSN1449369413
Descrizione libro Paperback. Condizione: BRAND NEW. BRAND NEW. Fast Shipping. Prompt Customer Service. Satisfaction guaranteed. Codice articolo 1449369413BNA
Descrizione libro O'Reilly Media, 2016. Condizione: New. A+ Customer service! Satisfaction Guaranteed! Book is in NEW condition. Codice articolo 1449369413-2-1
Descrizione libro O'Reilly Media 2016-05-25, 2016. Paperback. Condizione: New. Codice articolo 6666-GRD-9781449369415