mastering machine learning python von swamynathan manohar (8 Ergebnisse)

Zustand: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Paperback. Zustand: Fair. 1st ed. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.

Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.18.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Taschenbuch. Zustand: Neu. Neuware -Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. This updated version¿s approach is based on the ¿six degrees of separation¿ theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two parts: theoretical concepts and practical implementation using suitable Python 3 packages.Yoüll start with the fundamentals of Python 3 programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as exploratory analysis, feature dimension reduction, regressions, time series forecasting and their efficient implementation in Scikit-learn are covered as well. Yoüll also learn commonly used model diagnostic and tuning techniques. These include optimal probability cutoff point for class creation, variance, bias, bagging, boosting, ensemble voting, grid search, random search, Bayesian optimization, and the noise reduction technique for IoT data.Finally, yoüll review advanced text mining techniques, recommender systems, neural networks, deep learning, reinforcement learning techniques and their implementation. All the code presented in the book will be available in the form of iPython not Elektronisches Buch to enable you to try out these examples and extend them to your advantage.What You'll LearnUnderstand machine learning development and frameworksAssess model diagnosis and tuning in machine learningExamine text mining, natuarl language processing (NLP), and recommender systemsReview reinforcement learning and CNNWho This Book Is ForPython developers, data engineers, and machine learning engineers looking to expand their knowledge or career into machine learning area.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 476 pp. Englisch.

Zustand: New. In.

Paperback. Zustand: Brand New. 2nd edition. 474 pages. 10.00x7.00x1.00 inches. In Stock.