Machine Learning Notebooks

Tips & Tutorials

• A collection of not so obvious Python stuff you should know! [Jupyter Notebook]
• Python’s scope resolution for variable names and the LEGB rule [Jupyter Notebook]
• Key differences between Python 2.x and Python 3.x [Jupyter Notebook]
• A collection of useful regular expressions [Jupyter Notebook]
• A random collection of useful Python snippets [Jupyter Notebook]

Statistics

• Exploratory Data Analysis [Jupyter Notebook]
• Summary Statistics [Jupyter Notebook]
• Covariance and Correlation [Jupyter Notebook]
• Probability Mass Functions [Jupyter Notebook]
• Probability Density Functions [Jupyter Notebook]
• Least-Squares Linear Regression [Jupyter Notebook]
• Bootstrapping (Nonparametric Inference) [Jupyter Notebook]
• Hypothesis Testing Introduction [[Jupyter Notebook](https://github.com/rasbt/data-science-tutorial/blob/master/
• code/hypothesis-testing_1.ipynb)]

Scientific Computing

• Sorting CSV files using the Python csv module [Jupyter Notebook]
• Using Cython with and without IPython magic [Jupyter Notebook]
• Parallel processing via the multiprocessing module [Jupyter Notebook]
• Entry point: Data - using sci-packages to prepare data for Machine Learning tasks and other data analyses [Jupyter Notebook]
• Quick guide for dealing with missing numbers in NumPy [Jupyter Notebook]
• Converting large CSV files to SQLite databases using pandas [Jupyter Notebook]
• Sparsifying a matrix by zeroing out all elements but the top k elements in a row using NumPy [Jupyter Notebook]
• Things in pandas I wish I’d had known earlier [Jupyter Notebook]

Math & Algorithms

• Sorting Algorithms [Jupyter Notebook]
• Linear regression via the least squares fit method [Jupyter Notebook]
• Dixon’s Q test to identify outliers for small sample sizes [Jupyter Notebook]
• Rejection sampling [Jupyter Notebook]
• Counting points inside a hypercube [Jupyter Notebook]
• Vectorizing a classic for-loop in NumPy for calculating Euclidean distances [Jupyter Notebook]
• Maximum Pairwise Product [Jupyter Notebook]
• Fibonacci Numbers [Jupyter Notebook]
• Greatest Common Divisor [Jupyter Notebook ]
• Introduction to Greedy Algorithms [Jupyter Notebook]
• Introduction to Divide-and-Conquer Algorithms [ Jupyter Notebookviewer ]

Data Structures

• Singly Linked List [Jupyter Notebook]

Web

• Creating internal links in IPython Notebooks and Markdown docs [Jupyter Notebook]
• A Simple Barebones Flask Webapp Template [GitHub Dir]

Benchmarks

• 1 - Reversing strings [Jupyter Notebook]
• 2 - Calculating sample means [Jupyter Notebook]
• 3 - 6 different ways to count elements using a dict [Jupyter Notebook]
• 4.1 - Python vs. Cython vs. Numba [Jupyter Notebook]
• 4.2 - (C)Python compilers - Cython vs. Numba vs. Parakeet [Jupyter Notebook]
• 5 - Comparing 9 ways for flattening lists of sublists [Jupyter Notebook]
• 6 - Determining if a string is a number [Jupyter Notebook]
• 7.1 - Speeding up NumPy array expressions with Numexpr [Jupyter Notebook]
• 7.2 - Just-in-time compilers for NumPy array expressions [Jupyter Notebook]
• 8 - Calculating square roots and exponents [Jupyter Notebook]
• 9 - The most Pythonic way to check if a string ends with a particular substring [Jupyter Notebook]
• 10 - Cython - Bridging the gap between Python and Fortran [Jupyter Notebook]
• 11 - The deque container data type Jupyter Notebook]
• 12 - Lightning fast insertion into sorted lists via the bisect module [Jupyter Notebook]
• 13 - Parallel processing via the multiprocessing module [Jupyter Notebook]
• 14 - Python’s and NumPy’s in-place operator functions [Jupyter Notebook]
• 15 - Array indexing in NumPy: Extracting rows and columns [Jupyter Notebook]
• 16 - Vectorizing a classic for-loop in NumPy [Jupyter Notebook]
• 17 - Stacking NumPy arrays [Jupyter Notebook]
• 18 - The scikit-learn preprocessing module for feature scaling [Jupyter Notebook]
• 19 - Python 2.7.x’s izip and xrange [Jupyter Notebook]
• 20 - Calculating the difference between successive elements in a Python list [Jupyter Notebook]

Matplotlib

• 2D histograms / heat maps / levelplots [Jupyter Notebook]
• 3D Plots [Jupyter Notebook]
• Bar plots [Jupyter Notebook]
• Boxplots and Violinplots [Jupyter Notebook]
• Errorbar plots [Jupyter Notebook]
• Formatting I: subplots, markers, colors, axes [Jupyter Notebook]
• Formatting II: gridlines [Jupyter Notebook]
• Formatting III: What it takes to become a legend [Jupyter Notebook]
• Histograms [Jupyter Notebook]
• Line plots [Jupyter Notebook]
• Preparing Plots for Publication [Jupyter Notebook]
• Scatter plots [Jupyter Notebook]
• Special plots [Jupyter Notebook]
• Clustering - Heatmaps and Dendrograms [Jupyter Notebook]
• Tips and Tricks [Jupyter Notebook]