Building machine learning systems with Python :: explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow /
Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2018.
|
| Ausgabe: | Third edition. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you'll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems. By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks. |
| Beschreibung: | Previous edition published: 2015. |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| ISBN: | 9781788622226 1788622227 |
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| 505 | 0 | |a Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow -- Contributors -- Table of Contents -- Preface -- Chapter 1: Getting Started with Python Machine Learning -- Chapter 2: Classifying with Real-World Examples -- Chapter 3: Regression -- Chapter 4: Classification I -- Detecting Poor Answers -- Chapter 5: Dimensionality Reduction -- Chapter 6: Clustering -- Finding Related Posts -- Chapter 7: Recommendations -- Chapter 8: Artificial Neural Networks and Deep Learning -- Chapter 9: Classification II -- Sentiment Analysis -- Chapter 10: Topic Modeling -- Chapter 11: Classification III -- Music Genre Classification -- Chapter 12: Computer Vision -- Chapter 13: Reinforcement Learning -- Chapter 14: Bigger Data -- Where to Learn More About Machine Learning -- Other Books You May Enjoy -- Index. | |
| 520 | 3 | |a Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you'll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems. By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks. | |
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| author | Coelho, Luis Pedro Richert, Willi Brucher, Matthieu |
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| contents | Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow -- Contributors -- Table of Contents -- Preface -- Chapter 1: Getting Started with Python Machine Learning -- Chapter 2: Classifying with Real-World Examples -- Chapter 3: Regression -- Chapter 4: Classification I -- Detecting Poor Answers -- Chapter 5: Dimensionality Reduction -- Chapter 6: Clustering -- Finding Related Posts -- Chapter 7: Recommendations -- Chapter 8: Artificial Neural Networks and Deep Learning -- Chapter 9: Classification II -- Sentiment Analysis -- Chapter 10: Topic Modeling -- Chapter 11: Classification III -- Music Genre Classification -- Chapter 12: Computer Vision -- Chapter 13: Reinforcement Learning -- Chapter 14: Bigger Data -- Where to Learn More About Machine Learning -- Other Books You May Enjoy -- Index. |
| ctrlnum | (OCoLC)1050169894 |
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| discipline | Informatik |
| edition | Third edition. |
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| spelling | Coelho, Luis Pedro, author. https://id.oclc.org/worldcat/entity/E39PCjDfqY8WWrhrRmrBTPDC33 http://id.loc.gov/authorities/names/no2013130479 Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow / Luis Pedro Coelho, Willi Richert, Matthieu Brucher. Third edition. Birmingham, UK : Packt Publishing, 2018. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Description based on online resource; title from title page (Safari, viewed August 27, 2018). Previous edition published: 2015. Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow -- Contributors -- Table of Contents -- Preface -- Chapter 1: Getting Started with Python Machine Learning -- Chapter 2: Classifying with Real-World Examples -- Chapter 3: Regression -- Chapter 4: Classification I -- Detecting Poor Answers -- Chapter 5: Dimensionality Reduction -- Chapter 6: Clustering -- Finding Related Posts -- Chapter 7: Recommendations -- Chapter 8: Artificial Neural Networks and Deep Learning -- Chapter 9: Classification II -- Sentiment Analysis -- Chapter 10: Topic Modeling -- Chapter 11: Classification III -- Music Genre Classification -- Chapter 12: Computer Vision -- Chapter 13: Reinforcement Learning -- Chapter 14: Bigger Data -- Where to Learn More About Machine Learning -- Other Books You May Enjoy -- Index. Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you'll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems. By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Python (Langage de programmation) Apprentissage automatique. Intelligence artificielle. artificial intelligence. aat COMPUTERS / Programming Languages / Python bisacsh Artificial intelligence fast Machine learning fast Python (Computer program language) fast Python (Llenguatge de programació) lemac Aprenentatge automàtic. lemac Intel·ligència artificial. lemac Richert, Willi, author. https://id.oclc.org/worldcat/entity/E39PCjCtpMQrDTjCpKWJmDvCQq http://id.loc.gov/authorities/names/no2013130477 Brucher, Matthieu, author. has work: Building machine learning systems with Python (Text) https://id.oclc.org/worldcat/entity/E39PCFK9g48VCV4mMM8tRB8YMX https://id.oclc.org/worldcat/ontology/hasWork FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1862371 Volltext |
| spellingShingle | Coelho, Luis Pedro Richert, Willi Brucher, Matthieu Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow / Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow -- Contributors -- Table of Contents -- Preface -- Chapter 1: Getting Started with Python Machine Learning -- Chapter 2: Classifying with Real-World Examples -- Chapter 3: Regression -- Chapter 4: Classification I -- Detecting Poor Answers -- Chapter 5: Dimensionality Reduction -- Chapter 6: Clustering -- Finding Related Posts -- Chapter 7: Recommendations -- Chapter 8: Artificial Neural Networks and Deep Learning -- Chapter 9: Classification II -- Sentiment Analysis -- Chapter 10: Topic Modeling -- Chapter 11: Classification III -- Music Genre Classification -- Chapter 12: Computer Vision -- Chapter 13: Reinforcement Learning -- Chapter 14: Bigger Data -- Where to Learn More About Machine Learning -- Other Books You May Enjoy -- Index. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Python (Langage de programmation) Apprentissage automatique. Intelligence artificielle. artificial intelligence. aat COMPUTERS / Programming Languages / Python bisacsh Artificial intelligence fast Machine learning fast Python (Computer program language) fast Python (Llenguatge de programació) lemac Aprenentatge automàtic. lemac Intel·ligència artificial. lemac |
| subject_GND | http://id.loc.gov/authorities/subjects/sh96008834 http://id.loc.gov/authorities/subjects/sh85079324 http://id.loc.gov/authorities/subjects/sh85008180 |
| title | Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow / |
| title_auth | Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow / |
| title_exact_search | Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow / |
| title_full | Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow / Luis Pedro Coelho, Willi Richert, Matthieu Brucher. |
| title_fullStr | Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow / Luis Pedro Coelho, Willi Richert, Matthieu Brucher. |
| title_full_unstemmed | Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow / Luis Pedro Coelho, Willi Richert, Matthieu Brucher. |
| title_short | Building machine learning systems with Python : |
| title_sort | building machine learning systems with python explore machine learning and deep learning techniques for building intelligent systems using scikit learn and tensorflow |
| title_sub | explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow / |
| topic | Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Python (Langage de programmation) Apprentissage automatique. Intelligence artificielle. artificial intelligence. aat COMPUTERS / Programming Languages / Python bisacsh Artificial intelligence fast Machine learning fast Python (Computer program language) fast Python (Llenguatge de programació) lemac Aprenentatge automàtic. lemac Intel·ligència artificial. lemac |
| topic_facet | Python (Computer program language) Machine learning. Artificial intelligence. Python (Langage de programmation) Apprentissage automatique. Intelligence artificielle. artificial intelligence. COMPUTERS / Programming Languages / Python Artificial intelligence Machine learning Python (Llenguatge de programació) Aprenentatge automàtic. Intel·ligència artificial. |
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