On the other hand, Miniconda requires less disc space. The main difference is that Anaconda provides a graphical user interface (Anaconda navigator) and a whole lot of scientific packages (e.g ) when installing, whereas for Miniconda the user needs to install all packages using the command line. Note: When you are already familiar to the command line and Python environments you could opt to use Miniconda instead of Anaconda and download it from.

Recent computers will require the 64-Bit installer.įor more detailed instructions to install Anaconda, check the Windows, Mac or linux installation tutorial. Install Anacondaįor first time users and people not fully confident with using the command line, we advice to install Anaconda, by downloading and installing the Python 3.x version from. To install the required libraries, we highly recommend Anaconda or miniconda ( ) or another Python distribution that includes the scientific libraries (this recommendation applies to all platforms, so for both Window, Linux and Mac). The course uses Python 3 and some data analysis packages such as Numpy, Pandas, scikit-learn, matplotlib, and seaborn.

Use these principles by using the scikit-learn library on some toy and real-world data examples.

Get familiar with general principles of machine learning.

Goal: introduce the basics of machine learning using the scikit-learn library.

Introduction to the basics of numpy, pandas, and matplotlib.

Goal: introduce the PyData ecosystem to manipulate, explore, and visualize data. You can run the notebooks in a binder: Program Day 1 - Data wrangling, exploration, and visualisation Note: the material in this repo is WIP, not the finalized material. This workshop intends to give an introduction to some of these topics using Python and the PyData ecosystem. Data science encompasses a large number of topics such as data mining, data wrangling, data visualisation, pattern recognition, or machine learning.

$workshop data 2019$

Materials for the Paris-Saclay Center for Data Science python workshopĭata science is gaining attention impacting many scientific fields and applications. 2-Day Workshop - Introduction to Data Science in Python

Workshop data 2019