ax-va/Python-Machine-Learning-Recipes-Gallatin-Albon-2023
Machine learning recipes in Python with scikit-learn, OpenCV, PyTorch, and other libraries, including classical machine learning and neural networks, based on the book "Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning", Second Edition, by Kyle Gallatin and Chris Albon published by O'Reilly Media in 2023
This is a collection of practical, step-by-step examples for applying machine learning techniques to real-world data. It shows you how to take raw data, apply various machine learning algorithms like neural networks or classical models, and get meaningful predictions or classifications. Anyone looking to implement machine learning solutions, such as data analysts or researchers, would find this useful.
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Use this if you need concrete examples and code to help you apply machine learning concepts to your own datasets, from data preparation to model deployment.
Not ideal if you are looking for a conceptual overview of machine learning theory without practical coding examples.
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Apr 29, 2025
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