antahiap/dsr-time-series-02

Data Science with Python - exercises and tutorials

Teaching Data Science

Data Science with Python - exercises and tutorials about statistics, data handling and transformation, modelling, and machine learning models.

Intro to Statistics

We'll use some very helpful tools from packages scipy and statsmodels, which are really great and super comprehensive for statistics with Python.

Nice resources to learn more:

• Resampling http://www.resample.com/intro-text-online/ This is a very complehensive book about resampling “Resampling: The New Statistics” by Julian L. Simon (1997)
• Parametric vs. non-parametric models explained super well here: http://mlss.tuebingen.mpg.de/2015/slides/ghahramani/gp-neural-nets15.pdf
• Data distributions very very nice discussion in this thread here: https://www.quora.com/Most-machine-learning-datasets-are-in-Gaussian-distribution-Where-can-we-find-the-dataset-which-follows-Bernoulli-Poisson-gamma-beta-etc-distribution
• This awessome free book Gareth James,Daniela Witten, Trevor Hastie, Robert Tibshirani. An Introduction to Statistical Learning with Applications in R https://www.statlearning.com/

Timeseries predictive modelling

Introduction to classical and multivariate timeseries analyses

Creating data pipelines with PySpark and Koalas

Coming soon!

Credits for the awesome vector above: Cartoon vector created by vectorjuice - www.freepik.com