chhayac/Machine-Learning-Notebooks
15+ Machine/Deep Learning Projects in Ipython Notebooks
This is a collection of practical examples demonstrating how to apply machine learning to various real-world problems. It takes diverse datasets—like flower measurements, movie reviews, traffic signs, or customer data—and shows how to build models that can classify, predict, or recommend. This resource is for data scientists, analysts, or students who want to see concrete implementations of common machine learning tasks.
153 stars. No commits in the last 6 months.
Use this if you are a data science practitioner looking for runnable code examples to understand or adapt machine learning solutions for problems like image recognition, sentiment analysis, or customer churn prediction.
Not ideal if you are looking for a deployable, production-ready application or a detailed theoretical textbook on machine learning concepts.
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153
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Jupyter Notebook
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Last pushed
Apr 03, 2020
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