Python 3 for Machine Learning
本书旨在为读者提供与机器学习相关的基本 Python 3 编程概念。 前四章快速介绍了 Python 3、NumPy 和 Pandas。 第五章介绍了机器学习的基本概念。 第六章专门介绍机器学习分类器，例如逻辑回归、k-NN、决策树、随机森林和 SVM。 最后一章包括有关 NLP 和 RL 的材料。 包含基于 Keras 的代码示例以补充理论讨论。 本书还包含正则表达式、Keras 和 TensorFlow 2 的单独附录。(This book is designed to provide the reader with basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fundamental concepts of machine learning. The sixth chapter is devoted to machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on NLP and RL. Keras-based code samples are included to supplement the theoretical discussion. The book also contains separate appendices for regular expressions, Keras, and TensorFlow 2.)
页:
[1]