IPython (Interactive Python) is a command shell for interactive computing in multiple programming languages, originally developed for the Python programming language, that offers introspection, rich media, shell syntax, tab completion, and history. IPython provides the following features: * Interactive shells (terminal and Qt-based). * A browser-based notebook interface with support for code, text, mathematical expressions, inline plots and other media. * Support for interactive data visualization and use of GUI toolkits. * Flexible, embeddable interpreters to load into one's own projects. * Tools for parallel computing. IPython is a fiscally sponsored project. (Wikipedia).
006 Installing IPython in Linux
Here we take a quick look at installing the iPython notebook on Linux using the command line in the Terminal.
From playlist Introduction to Pyhton for mathematical programming
From playlist Miscellaneous
Project Jupyter provides notebooks not only for IPython, but also for many other computer languages as well. A name change was thus required from IPython notebooks to Jupyter notebooks. In this lesson I show you the new website where you can download and install IPython and also how to l
From playlist Learning medical statistics with python and Jupyter notebooks
Meeting of the Jupyter/IPython development team.
From playlist JupyterLab Documentation
Jupyter/IPython Dev Meeting, January 17, 2017
Meeting of the IPython/Jupyter development team, January 17, 2017 Meeting Notes: https://etherpad.wikimedia.org/p/Jupyter-Weekly-Team-Meetings-2017-01-Jan
From playlist Jupyter / IPython dev meetings
This one is famous! And super ancient. We aren't sure if old Pythag was the first to come up with it, but if not, he arrived at it independently of anyone prior, and his name is associated with it. It's quite nifty when you really think about it. Take a look! Watch the whole Mathematics p
From playlist Geometry
7 Rotation of reference frames
Ever wondered how to derive the rotation matrix for rotating reference frames? In this lecture I show you how to calculate new vector coordinates when rotating a reference frame (Cartesian coordinate system). In addition I look at how easy it is to do using the IPython notebook and SymPy
From playlist Life Science Math: Vectors
Setting up Python for machine learning: scikit-learn and Jupyter Notebook
Want to get started with machine learning in Python? I'll discuss the pros and cons of the scikit-learn library, show how to install my preferred Python distribution, and demonstrate the basic functionality of the Jupyter Notebook. If you don't yet know any Python, I'll also provide four r
From playlist Machine learning in Python with scikit-learn
The Emacs Ipython Notebook- John Miller (Honeywell UOP)
John Miller offers an overview of the Emacs IPython Notebook (EIN), a full-featured client for the Jupyter Notebook in Emacs, and shares a brief history of its development. John covers the features of EIN that make it uniquely Emacs—starting and automatically logging into a Jupyter server
From playlist JupyterCon in New York 2018
Jupyter: Kernels, Protocols, and the IPython Reference Implementation
Matthias Bussonnier (UC Berkeley BIDS), Paul Ivanov (Bloomberg LP) Matthias Bussonnier and Paul Ivanov walk you through the current Jupyter architecture and protocol and explain how kernels work (decoupled from but in communication with the environment for input and output, such as a note
From playlist JupyterCon
Summer App Space: Lecture 1 - Dr. C. Corbett Moran – 6/26/17
Introducing course objectives, software engineering, python interpreter, IPython console, bash console, Jupyter notebooks, objects, float, int, bool, string, None, type function, asking good questions, variables and assignment, operators, control flow, if statements, indentation, while loo
From playlist Summer App Space - 2017
IPython/Jupyter Dev Meeting, April 5, 2016
Meeting of the IPython/Jupyter development team.
From playlist Jupyter / IPython dev meetings
O'Reilly Webcast: Data Science Experiments with Twitter and IPython Notebook
Want to learn the basic skills to stop talking about data science and start doing data science? After attending this mini-workshop, you'll be able to run your own data science experiments with Twitter's API and IPython Notebook! Besides learning the fundamentals of how to use IPython Noteb
From playlist O'Reilly Webcasts 3
OSB 2015 - Introduction to data munging with pandas and IPython Notebook - Melissa Lewis
This talk will go over importing, exploring, and exporting your data, and common issues you may encounter.
From playlist Open Source Bridge 2015
Jupyter Frontends: From the Classic Jupyter Notebook to JupyterLab, nteract, and Beyond
Kyle Kelley (Netflix), Brian Granger (Cal Poly San Luis Obispo) offer a broad look at Jupyter frontends, describing their common aspects and explaining how their differences help Jupyter reach a broader set of users. They also share ongoing challenges in building these frontends (real-time
From playlist JupyterCon
Jupyter/IPython Dev Meeting, March 14, 2017
Meeting of the Jupyter/IPython development team, March 14, 2017 Meeting Notes: https://paper.dropbox.com/doc/March-2017-Jupyter-Weekly-Meetings-rLiXjbl77MPLNNpNB1hdu
From playlist Jupyter / IPython dev meetings
Python pandas — Intro & Installation -- Learning by Doing
Sometimes we learn best by doing. Unlike my other videos, I’ll be going through these exercises cold. Sometimes we’ll encounter ambiguous questions, and sometimes I'll be wrong. Learning from our mistakes can be a powerful teacher. So, it’s OK to be wrong now, because we’ll know how to
From playlist Python pandas -- Learning by doing