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Curated list of resources to help you get started with Data Science
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What is Data Science?
Differentiation of Big Data, Machine Learning, Data Science.
Common Algorithms and Procedures
The two most common types of Machine Learning algorithms.
Evaluate the performance of your algorithm / model.
Modifying the data to better model predictions.
Data processing, implementation, and visualization with example code.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Various other helpful tools and resources
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Completely free enterprise-ready Python distribution for large-scale data processing, predictive analytics, and scientific computing
A library for industrial-strength natural language processing in Python and Cython.
Data Science Challenges for Beginners
Walkthrough through a simple challenge on house prices.
Predict if a donor will donate again.
More advanced resources and lists
An awesome Data Science repository to learn and apply for real world problems.
common data analysis and machine learning tasks using python
machine learning and deep learning tutorials, articles and other resources