Gallery of the best notebooks for ML and Data Science

Hello, reader.

I submit a post that goes strictly (!) To bookmarks and is transmitted to colleagues. It includes a selection of noteworthy Jupyter Notebook files on Machine Learning, Data Science, and other areas related to data analysis. These Jupyter notebooks will be most useful to data analysts, both beginners and practicing pros.


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So let's get started.

Introductory courses in Jupyter Notebook

• Python tutorial
• Selection of notebooks by IPython commands
• Matplotlib Handbook

Statistics, machine learning and data science

• Notepad for quantifying uncertainty and sensitivity analysis
• Accompanying Materials for Jake Wonderplas Book Python Data Science Handbook
• Introduction to statistics with Python
• Notebooks on the exercises of the online course Andrew Un on ML, Spark and TensorFlow
• Monte Carlo methods, stochastic optimization
• Introduction to Bayesian Output
• Bayesian data analysis
• Data Science Tutorial
• IPython Cookbook
• Introduction to machine learning with Python and scikit-learn
• A growing collection of notebooks at the University of Turin machine learning course
• Clustering and regression
• Neural networks
• Introduction to Pandas
• Data Science and Big Data with Python
• The Statsmodels project has two sets of notebooks: in the official documentation and in the wiki.
• Python to analyze data
• Statistics and data analysis for psychologists
• Solution of the task of a course on data analysis CS 109
• The book "Introduction to statistical training with applications in the language of R" has two collections of notebooks with examples in Python
• Exercise notebooks for the course of StatLearning
• Applied Predictive Modeling with Python
• A large selection of four courses on Data Science, algorithms and databases of the University of Colombia
• SciPy and OpenCV as an interactive computing environment for computer vision
• Kalman and Bayes filters on Python
• Adaboost for the task of classifying numbers
• A selection of practical use of machine learning and data analysis
• Deep learning with Apache SINGA
• A selection of notebooks for ML and Data Science
• ETL with Python, work with MySQL and csv files

SciPy data analysis

• Introduction to machine learning with sklearn
• Interactive curve fitting with lmfit package
• Introduction to machine learning with Python and scikit-learn
• Face Recognition (Dataset Wild)
• Introduction to Bayesian Multilevel Modeling Techniques
• Introduction to Bayesian Networks
• Bayesian data analysis with PyMC3
• A set of examples for solving template classification problems
• Probability, Paradox and the Principle of Reason
• Determination of 5 stars recall probability
• Geodemographic Segmentation Model

Data visualization and graphing in Jupyter Notebook

• Common problems when rendering large data sets and how to avoid them
• Visualization of US census data using datashader
• Integration of data and visualization using web resources
• 21 interactive graphics
• Visualization of complex functions with Matplotlib and Mayavi
• An example of using the bqplot library
• D3 Viewer for Matplotlib Visualization
• Bokeh - an interactive library for web visualization with Python
• Rendering with HoloViews
• Winner of E. Tufte Slope Graphs
• matta - d3.js visualization in IPython Notebook
• Pandas Display in an Interactive Value Distribution Map

Natural language processing

• Python programming for the humanities
• Multinomial naive Bayes news classifier
• Using random cross validation to categorize news

Pandas to analyze data in Jupyter Notebook

• 10 minute Pandas tour
• Time Series Analysis with Pandas
• Analyzing Financial Data with Pandas
• Clustering data from smartphone sensors to analyze physical activity data with pandas and scipy
• Analysis and visualization of flares on the sun
• Advanced Apache Log Analysis
• Statistical data analysis in Python
• Deep immersion in Pandas from .head () to .tail ()

If you have something you can share - write in the comments. More information about machine learning and Data Science in the Neuron telegram channel (@neurondata).

All knowledge!