This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems, from loading data...
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This book is meant as a textbook for undergraduate and graduate students who are willing to understand essential elements of machine learning from both a theoretical and a practical perspective. The choice of the topics in the book is made based on one criterion: whether the practical utility of...
该教科书涵盖了一系列主题,包括最近邻、线性模型、决策树、集成学习、模型评估和选择、降维、组装各种学习阶段、聚类和深度学习,并介绍了用于数据科学和计算的基本 Python 包。机器学习,例如 NumPy、Pandas、Matplotlib、Scikit-Learn、XGBoost 和带有 TensorFlow 后端的 Keras。鉴于 Python 编程语言目前在机器学习中的主导...
Book description 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...
it'scrucialtoknowhowamachine"learns"underthehood.Thisbookwillguideyouthroughtheimplementationandnuancesofmanypopularsupervisedmachinelearningalgorithmswhilefacilitatingadeepunderstandingalongtheway.You’llembarkonthisjourneywithaquickoverviewandseehowsupervisedmachinelearningdiffersfromunsupervisedlearning.Next,weexplore...
Machine Learning with PyTorch and Scikit-Learnhas been a long time in the making, and I am excited to finally get to talk about the release of my new book. Initially, this project started as the 4th edition ofPython Machine Learning. However, we made so many changes to the book that we...
Advanced Machine Learning with Python是John Hearty创作的计算机网络类小说,QQ阅读提供Advanced Machine Learning with Python部分章节免费在线阅读,此外还提供Advanced Machine Learning with Python全本在线阅读。
特征工程:特征工程是为了提取和选择对预测结果有影响的特征。你可以使用Python中的sklearn库来进行特征选择和转换。以下是一个使用特征选择算法的例子: fromsklearn.feature_selectionimportSelectKBestfromsklearn.feature_selectionimportchi2 X=data.iloc[:,:-1]# 特征y=data.iloc[:,-1]# 标签# 使用卡方检验选...
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