Machine Learning Algorithms Giuseppe Bonaccorso 著 更新时间:2021-07-02 18:54:04 开会员,本书免费读 >最新章节: 【正版无广】Summary 计算机网络 编程语言与程序设计 ThisbookisforITprofessionalswhowanttoenterthefieldofdatascienceandareverynewto
pythonmachine-learningalgorithmjupytermachine-learning-algorithmsjupyter-notebookmachinelearning UpdatedNov 12, 2024 Jupyter Notebook TheAlgorithms/C Star20.2k Code Issues Pull requests Discussions Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C...
About This Book Leverage Python' s most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust...
Examples and explanations using the scikit-learn machine learning library, which provides a wide variety of machine learning algorithms via a user-friendly Python API Discussions about the strengths and weaknesses of classifiers with linear and non-linear decision boundaries ...
The good part of the book is, it explains the application of algorithms and techniques with python code examples.(sklearn is the library of choice mostly).Cons:1. Less focus on mathematical derivations of the algorithms.2. Less information about deep learning.But since this is just an ...
PythonMachineLearningSecondEditionnowincludesthepopularTensorFlowdeeplearninglibrary.Thescikit-learncodehasalsobeenfullyupdatedtoincluderecentimprovementsandadditionstothisversatilemachinelearninglibrary.SebastianRaschkaandVahidMirjalili’suniqueinsightandexpertiseintroduceyoutomachinelearninganddeeplearningalgorithmsfromscratch,and...
I have a copy of the first edition of this book and originally used it for the consumer analytics applications it discusses. This book is really suited to those who wish to see exactly how machine learning algorithms are implemented (in pure Python) as opposed to being taught how to use a...
Chapter 3. A Tour of Machine Learning Classifiers Using scikit-learn In this chapter, we will take a tour through a selection of popular and powerful machine learning algorithms that are … - Selection from Python Machine Learning - Second Edition [Book
Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data Explores important classification and regression algorithms as well as other machine learning techniques Explains how to use Python to handle data extraction, manipulation, and exploration tec...
After completing the whole book you should be ready to face a project by yourself and be confortable with the different steps in this process. You will be able to code most if not all of the machine learning algorithms in Python, and understand what you are doing through the whole process...