Introduction to Data Science with Python

About the Site

This post is going to be a walkthrough of what this site is about and what content the following blog posts will consist of. The sites concept is an introduction into the python libraries used in data analysis/machine learning. It is split into four main parts:

  • Blog Posts

    Posts will mostly be small machine learning projects. They will go over all aspects from grabbing the data to creating a machine learning model for predictions. The goal of these posts are to help show all the different python libraries being used together and seeing the overall process when going through a machine learning problem.

  • Python Library Interactive Section

    For the given python library a basic introduction to it will be shown using code examples. The examples will be done using a dataset that will be described at the top of the page and thanks to DataCamp (check them out at there is an interactive shell where the code examples can be tried out and experimented with.

  • Python Library Informational Section

    There will be a short description about the given python library and what it is used for.

  • Machine Learning Algorithms

    This section will explain the various machine learning algorithms and show how they can be implemented using the python library scikit-learn.

About myself

Since I am the only one that will be posting on here I thought I should say a little bit about myself. My name is Brian and am currently a grad student studying Data Science. I have a Bachelors in Mathematics and Computer Science and would say that this site is about combining these interests together (this site is made with Django, a great Python Web framework). I think that Python is a great tool for Data Science and has all the libraries you need to start doing your own data analysis and machine learning projects. As this site is really just an introduction to these topics I would also recommend sites like datacamp, udemy, and coursera in order to build your skills.


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