Thoughtful machine learning test driven von kirk matthew (13 Ergebnisse)

Zustand: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

Zustand: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.

Paperback. Zustand: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Zustand: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

paperback. Zustand: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Zustand: New. In English.

Zustand: New. In English.

Paperback. Zustand: Brand New. 250 pages. 9.00x6.75x0.25 inches. In Stock.

Paperback. Zustand: Brand New. 200 pages. 9.25x7.00x0.50 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware - Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext.Featuring graphs and highlighted code examples throughout, the book features tests with Python's Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you're a software engineer or business analyst interested in data science, this book will help you:- Reference real-world examples to test each algorithm through engaging, hands-on exercises- Apply test-driven development (TDD) to write and run tests before you start coding- Explore techniques for improving your machine-learning models with data extraction and feature development- Watch out for the risks of machine learning, such as underfitting or overfitting data- Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms.…

Taschenbuch. Zustand: Neu. Neuware - Apply a fully test-driven approach to machine-learning algorithms, and save yourself the pain of missing mistakes in your analyses. Most data scientists have run an analysis and simply accepted any answer that wasn t an error message. But just because it runs doesn t mean it s correct. Missed mistakes can ruin research and harm reputations.All of that can be avoided by writing tests and building checks into your work. This book shows you how to write tests and build checks into their work. Using the Ruby programming language, software developers, business analysts, and CTOs will learn how to test machine-learning code, and understand what s happening 'behind the scenes.' Code machine-learning algorithms in a test-driven way Gain confidence to utilize machine learning Dissect algorithms from the granular pieces using unit tests Get real-world examples of utilizing machine learning code.…