Introduction to Machine Learning with Python: A Guide for Data Scientists
This book will teach you practical ways to build your own machine learning solutions, even as a beginner.
Introduction to Machine Learning with Python: A Guide for Data Scientists
vare #: 193172969

Introduction to Machine Learning with Python: A Guide for Data Scientists

vare #: 193172969

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This book will teach you practical ways to build your own machine learning solutions, even as a beginner.
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Shop Introduction to Machine Learning with Python: A Guide for Data Scientists online at a best price in NORGE. 1449369413
  • Introduction to Machine Learning with Python: A Guide for Data Scientists 1st Edition
  • By O'Reilly, a brand known for sharing the knowledge of experts
  • Comprehensive guide to machine learning for data scientists
  • Provides the necessary skills and understanding for success
  • Inspires companies and individuals to innovate and excel
  • Helps customers build the innovations that propel the world forward
Yayu0131ncu0131O'Reilly Media
Yayu0131nlanma Tarihi15 Kasu0131m 2016
Basku01311.
Dilu0130ngilizce
Basku0131 Uzunluu011fu392 sayfa
ISBN-101449369413
ISBN-13978-1449369415
Boyutlar17.53 x 1.78 x 23.11 cm

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Introduction to Machine Learning with Python: A Guide for Data Scientists

About This Item

Product Description: Unlock the power of machine learning with "Introduction to Machine Learning with Python: A Guide for Data Scientists (1st Edition)". Designed specifically for aspiring data scientists, this comprehensive guide serves as a valuable resource to master the essential concepts and techniques of machine learning using Python. Whether you are a beginner or an experienced professional in the field of data science, this book is packed with valuable insights and practical examples to enhance your understanding of machine learning algorithms, models, and techniques. With a focus on Python for data science, you'll learn how to leverage its powerful libraries such as NumPy, Pandas, and Scikit-learn to analyze and manipulate data efficiently. "Introduction to Machine Learning with Python" covers a wide range of topics including data analysis, data visualization, predictive analytics, big data analytics, and artificial intelligence.

You'll gain a deeper understanding of key concepts such as deep learning, natural language processing, reinforcement learning, supervised and unsupervised learning, classification algorithms, regression analysis, and more. Harness the full potential of machine learning by exploring advanced concepts including feature engineering, model evaluation, cross-validation, dimensionality reduction, clustering algorithms, neural networks, support vector machines, random forests, decision trees, ensemble learning, anomaly detection, time series analysis, recommendation systems, sentiment analysis, and data cleaning. Written by industry experts, this 1st edition guide is an invaluable resource for data scientists who want to stay ahead in the rapidly evolving field of machine learning. Maximize your career opportunities and develop your skills to solve complex data challenges with confidence. Take your first step towards becoming a proficient data scientist with "Introduction to Machine Learning with Python: A Guide for Data Scientists (1st Edition)". Order your copy today and embark on a transformative journey into the world of machine learning and Python for data science.

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İngilizce Baskı Sarah Guido Editorial Review

Introduction to Machine Learning with Python: A Guide for Data Scientists is a comprehensive resource published by O'Reilly Media on November 15, 2016. The book, spanning 392 pages, is designed for data scientists looking to deepen their understanding of machine learning concepts using Python. With an accessible approach, it guides readers through the essential algorithms and applications, making complex topics digestible. The book is well-structured, and many readers appreciate its practical examples that bridge theoretical concepts with real-world applications.

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Fordeler

  • Written by leading experts in the field
  • Suitable for beginners and experienced users
  • Covers practical examples extensively
  • Focus on Python programming for machine learning
  • Well-organized content for easy understanding

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  • Some readers may prefer more advanced topics

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