tanvipenumudy/Winter-Internship-Internity
Repository to keep track of work assigned on a daily basis
This collection of articles guides you through fundamental machine learning concepts, providing a clear path to understanding key algorithms and techniques. It starts with basic data handling and visualization, then progresses to common machine learning models like linear regression, k-NN, decision trees, and SVMs. Anyone looking to learn practical machine learning skills from the ground up, such as aspiring data scientists, analysts, or students, will find this beneficial.
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Use this if you are a beginner interested in learning machine learning concepts and how to apply them to real-world data tasks, with practical examples in Python.
Not ideal if you are an experienced machine learning practitioner looking for advanced research topics or production-ready codebases.
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Jan 27, 2021
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