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Hands-On Unsupervised Learning Using Python
How to Build Applied Machine Learning Solutions from Unlabeled Data
Taschenbuch von Ankur Patel
Sprache: Englisch

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Beschreibung
Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied; this is where unsupervised learning comes in. Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow using Keras. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data and gain deeper business insight, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets. All you need is programming and some machine learning experience to get started.
Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied; this is where unsupervised learning comes in. Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow using Keras. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data and gain deeper business insight, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets. All you need is programming and some machine learning experience to get started.
Über den Autor

Ankur Patel is an applied machine learning researcher and data scientist with expertise in financial markets. His work focuses on unsupervised learning, natural language processing, time series prediction, and sequential data problems. Currently, Ankur finds hidden patterns in large-scale unlabeled data for clients around the world as a data scientist at ThetaRay, an Israeli artificial intelligence firm. Ankur started his career as the lead emerging markets trader at Bridgewater Associates and later founded and managed the machine learning-based hedge fund R-Squared Macro.

Details
Erscheinungsjahr: 2019
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 359
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781492035640
ISBN-10: 1492035645
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Patel, Ankur
Hersteller: O'Reilly Media
Maße: 233 x 183 x 22 mm
Von/Mit: Ankur Patel
Erscheinungsdatum: 16.04.2019
Gewicht: 0,64 kg
preigu-id: 115017371
Über den Autor

Ankur Patel is an applied machine learning researcher and data scientist with expertise in financial markets. His work focuses on unsupervised learning, natural language processing, time series prediction, and sequential data problems. Currently, Ankur finds hidden patterns in large-scale unlabeled data for clients around the world as a data scientist at ThetaRay, an Israeli artificial intelligence firm. Ankur started his career as the lead emerging markets trader at Bridgewater Associates and later founded and managed the machine learning-based hedge fund R-Squared Macro.

Details
Erscheinungsjahr: 2019
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 359
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781492035640
ISBN-10: 1492035645
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Patel, Ankur
Hersteller: O'Reilly Media
Maße: 233 x 183 x 22 mm
Von/Mit: Ankur Patel
Erscheinungsdatum: 16.04.2019
Gewicht: 0,64 kg
preigu-id: 115017371
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