Аннотация
Topics included: Introduction, Code Formatting, and Tools • Pythonic Code • General Traits of Good Code • The SOLID Principles • Using Decorators to Improve Our Code • Getting More Out of Our Objects with Descriptors • Using Generators • Unit Testing and Refactoring • Common Design Patterns • Clean Architecture
![Machine Learning with Python Cookbook [Practical Solutions from Preprocessing to Deep Learning]](https://www.rulit.me/data/programs/images/machine-learning-with-python-cookbook-practical-solutions-fr_554389.jpg "This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading...")
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