JupyterLab is a very powerful tool for research and teaching. In this session we will provide a brief overview of the main capabilities of JupyterLab and Jupyter Notebooks with a focus on Data Science applications. JupyterLab provides full support for Jupyter Notebooks and add powerful capabilities, such as text editors, terminals, data file viewers, interactive plotting, etc. Scikit-learn - Python package that allows to do machine learning.JupyterLab can be viewed as the evolution of the Jupyter Notebooks, an open-source web application that allows combining interactive code (Python, R, Matlab, C++, etc.), equations, text and rich outputs. Largest difference with Numpy is that it allows to have indices on the axis. Pandas - Python package that provides convenient functions that deal with tabular data. Numpy - Python package that provides convenient functions that deal with (multi-dimensional) arrays. Miniconda is just like Anaconda, but with less packages pre-installed. An additional advantage of Anaconda is that it will create its own virtual environment and hence will not mess with any system-installed Python version. Anaconda allows to automate the installing of dependencies and the updating of packages. Jupyter Lab is very alike Jupyter Notebook.Īnaconda (Miniconda) - As explained, Python has become one of the major programming languages because many packages are available. Specific for Jupyter Notebooks is that you can create reports with it at ease, since you can combine code with text and images. Jupyter Notebook - This is one of the many IDE that are available for Python. The most notable of these packages are Pandas, Numpy and Scikit-learn. Because a lot of science packages are available for Python, it is a popular language used by scientists in all kind of disciplines. Python - Programming language created by Guido van Rossum. It is far better integrated in Windows than traditional virtual machines. WSL - The Windows Subsystem for Linux is a virtual machine that runs within Windows and allows to setup Linux systems. A guideline on how to do this will be added later. Windows users may wish to install Windows Subsystem for Linux for these purposes. Usually it is easier to troubleshoot problems when a UNIX system is used. This guideline intends to help students install Jupyter on their Windows PC in an easy way. How to install Jupyter on Windows How to install Jupyter on Windows
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