The following IPython Notebooks are the standard training material distributed with the Addfor trainings. For more information about standard and custom training solutions please visit Services @ Addfor.

All the IPython notebooks are distributed under the Creative Commons Attribution-ShareAlike 4.0 International License.

For detailed installation instructions visit: Training material guidelines @ Addfor

All notebooks use our Addutils library: please install Addutils before running the Notebooks.

We recommend to install the Anaconda distribution to the latest version: please visit continuum.io to download Anaconda.

1. Python + IPython/Jupyter
   1. An introduction to the IPython notebook
   2. Python Basic Concepts
   3. Python Getting Started
   4. Python Style Guide
   5. Python More Examples
   6. Object Oriented Programming in Python
   7. Integration of Python with compiled languages
   8. Unicode
   9. Regular Expressions
2. NumPy
   1. Numpy Basic Concepts
   2. PyTables
   3. Numpy - Plotting with Matplotlib
   4. Scipy - Optimization
   5. Scipy Signal Processing: IIR Filter Design
   6. Symbolic Computation
3. Pandas
   1. pandas Dataframe - Basic Operativity
   2. pandas I/O tools and examples
   3. Pandas Time series
   4. Statistical tools
   5. Merge and pivot
   6. Split apply and combine
   7. Sources of Open Data
   8. Baby Names
4. Machine learning
   1. Definitions and Advices
   2. Prepare the Data
   3. The scikit-learn interface
   4. Visualizing the Data
   5. Dealing with Bias and Variance
   6. Ensemble Methods
   7. Support vector machines (SVMs)
   8. Predict Temporal Series