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berkeley_datascience

Taking MOOC, Foundations of Data Science: Computational Thinking with Python. Using standard modules (ie. sklearn, pandas, seaborn) rather than Berkeley's datascience module provided by instructors.

concrete_nlp_tutorial

An NLP workshop about concrete solutions to real problems

data-science-from-scratch

code for Data Science From Scratch book

github-tutorial

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

kaggle_learn

My notes and exercises from working through Kaggle-learn tutorials. Machine Learning, Pandas, Data Visualization and Deep Learning.

leetcode

Practicing programming fundamentals and algorithmic thinking by solving LeetCode problems in Python.

python_algorithms

My notes and exercises from "Problem Solving with Algorithms and Data Structures using Python"

stats

My notes and exercises from working through an Introductory Statistics text and implementing my solutions in Python.

swe-barebones

union_students

Exploration, visualization and inferential statistics on student data. In particular, data on students who graduated between the 13-14 and 17-18 academic years with a major in mathematics from Union College.