marcosbenicio/ML-zoomcamp
Homeworks and notes from the Machine Learning Zoomcamp course
This collection of Jupyter notebooks provides practical implementations and mathematical foundations for various machine learning algorithms. It guides users through creating models for tasks like car price prediction, customer churn forecasting, and identifying diabetes risk factors. Data scientists, machine learning engineers, and analysts looking to deepen their understanding and build real-world models would find this valuable.
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Use this if you are a data scientist or machine learning practitioner looking for hands-on examples and theoretical explanations for common ML tasks, from model building to deployment.
Not ideal if you are looking for a plug-and-play solution for a specific business problem without needing to understand the underlying machine learning concepts.
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Feb 03, 2024
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