Python数据分析和机器学习实践
这本书结合了机器学习、数据分析和 Python 语言，通过示例解释了如何以易于理解的方式将算法应用于现实S界的任务。全书共20章，大致分为4个部分。第一部分介绍Python工具包，包括科学计算库Numpy、数据分析库Pandas、可视化库Matplotlib；第二部分讲解机器学习中的经典算法，如回归算法、决策树、集成算法、支持向量机、聚类算法等；第三部分介绍了深度学习中常用的算法，包括神经网络、卷积神经网络和循环神经网络；第四部分是实际项目，基于真实数据集，将算法模型应用到实际业务中。
本书适合对人工智能、机器学习、数据分析等感兴趣的初学者和爱好者。
(This book combines machine learning, data analysis and python language, and explains how to apply algorithms to real-world tasks in an easy to understand way through examples.The book consists of 20 chapters and is roughly divided into four parts. The first part introduces Python toolkit, including scientific computing library numpy, data analysis library pandas and visualization library Matplotlib; The second part explains the classical algorithms in machine learning, such as regression algorithm, decision tree, integration algorithm, support vector machine, clustering algorithm, etc; The third part introduces the commonly used algorithms in deep learning, including neural network, convolutional neural network and cyclic neural network; The fourth part is the actual project, which applies the algorithm model to the actual business based on the real data set.This book is suitable for beginners and enthusiasts interested in artificial intelligence, machine learning, data analysis and so on.)
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