Python in Machine Learning: A Practical Guide
This blog explains how Python in Machine Learning is used in real-world projects, covering each stage from data cleaning and feature preparation to model training and prediction. It discusses key Python libraries such as NumPy, pandas, scikit-learn, and TensorFlow, and how they support algorithm building and testing.
The blog also gives a clear overview of practical workflows, helping readers understand how data, code, and models interact in everyday machine learning development.
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