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On Machine Learning and Programming Languages
This article was co-written by Mike Innes (Julia Computing), David Barber (UCL), Tim Besard (UGent), James Bradbury (Salesforce Research), Valentin Churavy (MIT), Simon Danisch (MIT), Alan Edelman (MIT), Stefan Karpinski (Julia Computing), Jon Malmaud (MIT), Jarrett Revels (MIT), Viral Shah (Julia Computing), Pontus Stenetorp (UCL) and... Read more
Ripyr: Sampled Metrics on Datasets Using Python’s Asuncio
Today I’d like to introduce a little python library I’ve toyed around with here and there for the past year or so, ripyr. Originally it was written just as an excuse to try out some newer features in modern python: asyncio and type hinting. The whole... Read more
Web Scraping with Python — Part Two — Library overview of requests, urllib2, BeautifulSoup, lxml, Scrapy, and more!
Welcome to part 2 of the Big-Ish Data general web scraping writeups! I wrote the first one a little bit ago, got some good feedback, and figured I should take some time to go through some of the many Python libraries that you can use for scraping,... Read more
General Tips for Web Scraping with Python
The great majority of the projects about machine learning or data analysis I write about here on Bigish-Data have an initial step of scraping data from websites. And since I get a bunch of contact emails asking me to give them either the data I’ve scraped myself, or... Read more
The ODSC team was delighted to present the second Outstanding Data Science Project Award to ‘Pandas’ at ODSC West on November 3rd.    Why ODSC is gives these awards… Most data scientists/developers use an open source language, tool, software or platform daily. All of these resources... Read more
The Incredible Growth of Python
We recently explored how wealthy countries (those defined as high-income by the World Bank) tend to visit a different set of technologies than the rest of the world. Among the largest differences we saw was in the programming language Python. When we focus on high-income countries, the growth of Python... Read more
Thomas originally posted this article here at http://twiecki.github.io  We recently released PyMC3 3.1 after the first stable 3.0 release in January 2017. You can update either via pip install pymc3 or via conda install -c conda-forge pymc3. A lot is happening in PyMC3-land. One thing I am particularily proud of is the developer... Read more
2 Ways to Implement Multinomial Logistic Regression in Python
Logistic regression is one of the most popular supervised classification algorithm. This classification algorithm mostly used for solving binary classification problems. People follow the myth that logistic regression is only useful for the binary classification problems. Which is not true. Logistic regression algorithm can also use to solve the multi-classification... Read more
What is knyfe?
Knyfe is a python utility for rapid exploration of datasets. Use it when you have some kind of dataset and you want to get a feel for how it is composed, run some simple tests on it, or prepare it for further processing. The great thing... Read more
Another batch of Think Stats notebooks
Getting ready to teach Data Science in the spring, I am going back through Think Stats and updating the Jupyter notebooks.  When I am done, each chapter will have a notebook that shows the examples from the book along with some small exercises, with more substantial... Read more