此内容来自第三方平台 (Dailymotion)。如果此视频侵犯了您的版权，请使用 立即删除 工具。
Introduction to Machine Learning with Python: A Guide for Data Scientists For Kindle
描述
Click Here : https://waiting-009.blogspot.com/?book=1449369413
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills
关键词与标签
相关视频
[GIFT IDEAS] Introduction to Machine Learning with Python: A Guide for Data Scientists
hikiusadwkew
Library Introduction to Machine Learning with Python: A Guide for Data Scientists - Andreas C.
khamren
Full version Introduction to Machine Learning with Python: A Guide for Data Scientists For Free
dm_c59f566b20e6503366c9f38d486d15f1
Full E-book Introduction to Machine Learning with Python: A Guide for Data Scientists Review
colmusikno
AWS Certified Machine Learning – Specialty (MLS-C01) 🚀 Master ML on AWS ✅ Data Engineering Model Building MLOps ✅ For ML Engineers, Data Scientists, AI Developers 🕒 180 mins 💲 $300 📚 1–2 Y
ExamKill Official
IBM Scientists Develop Algorithm to Accelerate Machine Learning Training
Artificial Intelligence