- Main
- Computers - Artificial Intelligence (AI)
- Machine Learning with Python Cookbook,...
Machine Learning with Python Cookbook, 2nd Edition (4th Early Release)
Kyle Gallatin, Chris AlbonThis 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 all the way from loading data to training models and leveraging neural networks.
Each recipe in this updated edition includes code that you can copy, paste, and run with a toy dataset to ensure it works. From there, you can adapt these recipes according to your use case or application. Recipes include a discussion that explains the solution and provides meaningful context. Go beyond theory and concepts by learning the nuts and bolts you need to construct working machine learning applications.
You'll find recipes for
Vectors, matrices, and arrays
Working with data from CSV, JSON, SQL, databases, cloud storage, and other sources
Handling numerical and categorical data, text, images, and dates and times
Dimensionality reduction using feature extraction or feature selection
Model evaluation and selection
Linear and logical regression, trees and forests, and k-nearest neighbors
Support vector machines (SVM), naive Bayes, clustering, and tree-based models
Saving and loading trained models from multiple frameworks
该文件将通过电报信使发送给您。 您最多可能需要 1-5 分钟才能收到它。
注意:确保您已将您的帐户链接到 Z-Library Telegram 机器人。
该文件将发送到您的 Kindle 帐户。 您最多可能需要 1-5 分钟才能收到它。
请注意:您需要验证要发送到Kindle的每本书。检查您的邮箱中是否有来自亚马逊Kindle的验证电子邮件。