Contemporary Machine Learning Methods: Harnessing Scikit-Learn and TensorFlow

| Titolo | Contemporary Machine Learning Methods: Harnessing Scikit-Learn and TensorFlow | Autore | Adam Jones | Prezzo | € 9,49 | Editore | Walzone Press | Lingua | Testo in Inglese | Formato | DRMFREE | |
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Descrizione |
"Contemporary Machine Learning Methods: Harnessing Scikit-Learn and TensorFlow" is an indispensable resource for data scientists and machine learning practitioners eager to sharpen their skills and stay at the forefront of technology. This book offers a comprehensive exploration of modern machine learning methodologies, encompassing innovative regression and classification techniques, along with complex neural network architectures using TensorFlow.
Explore practical implementations and real-world examples that demystify intricate concepts like unsupervised learning, deep learning optimizations, natural language processing, and feature engineering with clarity. Each chapter serves as a step-by-step guide to applying these contemporary methods, complete with code samples and thorough explanations.
Whether you're a professional aiming to deploy machine learning solutions at an enterprise level, an academic researcher investigating computational innovations, or a postgraduate student interested in cutting-edge AI, this book equips you with the insights, tools, and expertise needed to effectively leverage machine learning technologies. Master the nuances of machine learning with "Contemporary Machine Learning Methods: Harnessing Scikit-Learn and TensorFlow" and convert data into impactful knowledge.
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