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R , Python, Machine Learning, Data Analysis, Data Visualization,Data Manipulation,Data Cleaning

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data-science's Introduction

Data Science Handbook Cribsheet

Intro to Numpy, Pandas, Matplotlib and Scikit-Learn. Condensed from Python Data Science Handbook (@jakevdp)

book cover

iPython NumPy Pandas Matplotlib Scikit-Learn
Help & docs Datatypes Pandas objects Line plots Intro to ML
Keyboard shortcuts Arrays Indexing & selection Scatter plots Intro to Scikit-Learn
Magic commands Universal functions Data operations Error Bars Hyperparameters & Model validation
Input & output history Aggregations Missing data Density & contour plots Feature engineering
Shell commands Broadcasting Hierarchical indexing Histograms, bins & densities Naive Bayes
Errors & debugging Comparisons, masks, boolean logic Concat & append Plot legends Linear regression
Profiling & timing Fancy indexing Merge & join Colorbars Support vector machines (SVM)
Resources Sorting arrays Aggregation & grouping Subplots Decision trees & Random forests
Structured data Pivot tables Text & Annotation Principal component analysis (PCA)
Vectorized strings Custom Tickmarks Manifold learning
Time series Configs & stylesheets K-Means clustering
High-performance ops: eval(), query() 3D plotting Gaussian mixtures
Geo data with Basemap TO DO:Kernel density estimation (KDE)
Visualization with Seaborn TO DO:Face detection pipeline
Resources

data-science's People

Contributors

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