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Great work deserves to be shared. Especially in data science.
Each week, I'll curate three gems from the data science community:🗄️ Re: Remarkable Repository 💻 P: Prolific Programmer 🏢 O: Outstanding OrganizationI hope you find them as valuable and insightful as I do.
You can find all recommendations in the GitHub repository at finnoh/repo!
pymc-labs/CausalPy
🗄️ Repository | Causal Inference for quasi-experiments
The module CausalPy is built for causal inference in quasi-experimental settings in Python.
This is what the output can look like, in this case for a synthetic control variable approach. There are multiple other settings implemented, such as Difference-in-Difference, Regression Discontinuity, or Interrupted Time Series.
For a more detailed introduction, you can watch this video Benjamin Vincent, one of the module's developers.
Consider leaving a star! ⭐️
DataMania (Lillian Pierson)
💻 Programmer | Data Science for Marketing in Business
On Data Mainia’s blog, you can find a large collection of articles from using AI in your business to building a data science startup. This website is certainly more on the business and marketing side of things, which is a nice change considering that there are many personal blogs going into technical problems.
According to the About page, founder Lillian Pierson travels the world while running this online business. Giving the About page and her personal story a read is worth it!
freeCodeCamp
🏢 Organization | Learn to program, for free!
On freeCodeCamp.org you can learn about website design, JavaScript, Databases, Python, TensorFlow, Information Security, and more in over 9,000 tutorials.
Also take a look at their Project Euler problems, which is a large collection of mathematical problems for you to solve in your favorite programming language. These will certainly harden your analytical thinking skills and help to bring your ideas into computer code!
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