awesome-learn-datascience

Differentiation of Big Data, Machine Learning, Data Science

An introduction to Data Science and its use as a business asset

Technical Skills for the Data Science: This emphasizes the practical skills needed throughout the data science process

The two most common types of Machine Learning algorithms

Evaluate the performance of your algorithm/model

Modifying the data to better model predictions

Combine multiple models into one for better performance

Data processing, implementation, and visualization with example code

Online Course using Python that covers most of the relevant toolkits

Paid course, but 30 free days upon account creation (enough to complete course)

Pandas cheatsheet

Quick overview over the most important functions

Plot library that works great with Jupyter

Contains most of the important Python packages for Data Science

Open source toolkit for working with text-based data

LightGBM gradient boosting framework

Successfully used in many Kaggle challenges

Rent cloud servers for more timeconsuming calculations (r4.xlarge server is a good place to start)

Walkthrough through a simple challenge on house prices

Predict if a donor will donate again

Predict survival on the Titanic

Predict the operating condition of water pumps in Africa