data-science-learning-path
github.com/data-folks/data-science-learning-path ↗Data Science Learning Path - A complete guide to learn data science for beginners
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ProgrammingMathematics & StatisticsMachine LearningEvaluation MetricsDeep LearningNLP & NLUBook References
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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me supervised learning resources from data-science-learning-path"
Installation instructions →What's inside
Evaluation Metrics
- AccuracySupervised Learning
- Confusion MatrixSupervised Learning
- Elbow MethodUnsupervised Learning
- F ScoreSupervised Learning
- Hamming LossSupervised Learning
- MAESupervised Learning
Deep Learning
Machine Learning
- AdaBoostSupervised Learning
- Bagging ClassifierSupervised Learning
- CASE STUDY: Credit ScoringSupervised Learning
- CASE STUDY: House PricingSupervised Learning
- CASE STUDY: TitanicSupervised Learning
- CatBoostSupervised Learning
Book References
Programming
- Basic Python
- Git
- Github
BitbucketGitlab
- Hackerrank
LeetcodeKattis
- Intro to DBMS
- Object-oriented Programming
Mathematics & Statistics
Showing a sample of 71 resources. View the full list on GitHub →