Mat Leonard earned a PhD in Physics from UC Berkeley, where he wrote his dissertation on neural activity related to short term memory. When it came time to make sense of his data, he turned to Python and the science stack including Numpy, Scikit-learn, and Pandas. He created his personal blog, Matatat.org, to publish small data projects online. For example, he explored linear regression models for predicting body fat percentage and a Bayesian approach to A/B testing.And with all that said, here is Mat on our subject for today!
Putting Your Small Data Projects Online
At our recent Intersect summit, a student asked me how to gain the data analysis experience needed to land a job. My suggestion was to work on small data analysis projects then put them online, as I did with my blog. Small projects let you deepen your understanding of analysis methods or learn new techniques. Publishing them online builds a portfolio of your work, showing potential employers that you can successfully answer questions with data.There are a few bits of technology that make getting your projects online a simple process. Firstly, Jupyter notebooks are an excellent tool for combining text, code, and images. Notebooks can be converted to Markdown files for use with web frameworks, such as Pelican. Finally, you can host your blog for free on GitHub. For the information to follow, you’ll need to know basic usage of git and GitHub: how to stage, commit, and push changes. You can learn about git and GitHub in our excellent course on version control. You’ll also need to be comfortable working from the command line, which you can learn about here.Building Your Blog
To build the blog itself, you can use Pelican, a static site generator written in Python. Pelican uses the Markdown files as blog posts and automatically creates an archive, categories, and tags. There are multiple themes to use with Pelican or you can make your own for a unique and personal touch.To know more visit our site http://allindiayellowpage.com/.