Data Science

My data science projects/notebooks using Python and R. Some of the projects e.g. Omdena-WFP are meant to develop novel methods for providing solution to a real world problem. The projects cover the following skills:

Machine Learning

• Ensemble Methods in Python
• Extreme Gradient Boosting with XGBoost
• Case Study: School Budgeting with Machine Learning in Python
• Cluster Analysis in Python
• Unsupervised Learning in Python
• Hyperparameter Tuning in Python
• Machine Learning with Tree-Based Models in Python
• Linear Classifers in Python
• Supervised Learning with scikit-learn

Statistical Inference

• Statistical Thinking in Python (Part 2)
• Statistical Thinking in Python (Part 1)

Data Analysis and Visualization

• Case Study: Analyzing Police Activity with pandas
• Exploratory Data Analysis in Python
• Data Visualization with Seaborn
• Data Visualization with Matplotlib

Data Manipulation with Python

• Working with Dates and Times in Python
• Merging DataFrames with pandas
• Manipulating DataFrames with pandas

Importing & Cleaning Data

• Cleaning Data in Python
• Intermediate Importing Data in Python
• Introduction to Importing Data in Python

Python Programming

• Object Oriented Programming in Python
• Python Data Science Toolbox (Part 2)
• Python Data Science Toolbox (Part 1)
• Intermediate Python
• Introduction to Python

Reference:

1. Applied Data Science, World Quant University and The Data Incubator.
2. Data Scientist with Python Career Track- Datacamp
3. R Graphics Cookbook by Winston Chang.
4. R for Data Science by Garrett Grolemund and Hadley Wickham.