product
1324042Thoughtful Machine Learning with Pythonhttps://www.gandhi.com.mx/thoughtful-machine-learning-with-python-1/phttps://gandhi.vtexassets.com/arquivos/ids/381225/34c978a4-8db8-4a6c-9302-b1a77248b175.jpg?v=638334467884230000356494MXNOReilly MediaInStock/Ebooks/<p>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.</p><p>Featuring graphs and highlighted code examples throughout, the book features tests with Pythons Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If youre a software engineer or business analyst interested in data science, this book will help you:</p><ul><li>Reference real-world examples to test each algorithm through engaging, hands-on exercises</li><li>Apply test-driven development (TDD) to write and run tests before you start coding</li><li>Explore techniques for improving your machine-learning models with data extraction and feature development</li><li>Watch out for the risks of machine learning, such as underfitting or overfitting data</li><li>Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms</li></ul>...1313151Thoughtful Machine Learning with Python356494https://www.gandhi.com.mx/thoughtful-machine-learning-with-python-1/phttps://gandhi.vtexassets.com/arquivos/ids/381225/34c978a4-8db8-4a6c-9302-b1a77248b175.jpg?v=638334467884230000InStockMXN99999DIEbook20179781491924082_W3siaWQiOiIyZTZhZjQxZC1jNTNlLTQ3OGItODVkMy1jYWRlZDRlNWU1NzQiLCJsaXN0UHJpY2UiOjQ5NCwiZGlzY291bnQiOjEzOCwic2VsbGluZ1ByaWNlIjozNTYsImluY2x1ZGVzVGF4Ijp0cnVlLCJwcmljZVR5cGUiOiJXaG9sZXNhbGUiLCJjdXJyZW5jeSI6Ik1YTiIsImZyb20iOiIyMDI0LTA1LTE4VDA0OjAwOjAwWiIsInJlZ2lvbiI6Ik1YIiwiaXNQcmVvcmRlciI6ZmFsc2V9XQ==9781491924082_<p>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.</p><p>Featuring graphs and highlighted code examples throughout, the book features tests with Pythons Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If youre a software engineer or business analyst interested in data science, this book will help you:</p><ul><li>Reference real-world examples to test each algorithm through engaging, hands-on exercises</li><li>Apply test-driven development (TDD) to write and run tests before you start coding</li><li>Explore techniques for improving your machine-learning models with data extraction and feature development</li><li>Watch out for the risks of machine learning, such as underfitting or overfitting data</li><li>Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms</li></ul>(*_*)9781491924082_<p>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.</p><p>Featuring graphs and highlighted code examples throughout, the book features tests with Pythons Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If youre a software engineer or business analyst interested in data science, this book will help you:</p><ul><li>Reference real-world examples to test each algorithm through engaging, hands-on exercises</li><li>Apply test-driven development (TDD) to write and run tests before you start coding</li><li>Explore techniques for improving your machine-learning models with data extraction and feature development</li><li>Watch out for the risks of machine learning, such as underfitting or overfitting data</li><li>Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms</li></ul>...9781491924082_OReilly Medialibro_electonico_55e96ab7-44d8-3608-b4f7-e1582e982fb4_9781491924082;9781491924082_9781491924082Matthew KirkInglésMéxicohttps://getbook.kobo.com/koboid-prod-public/oreilly-epub-e3c3ddc8-c589-4bd3-90de-ebf25c8a8050.epub2017-01-16T00:00:00+00:00OReilly Media