Introduction to Data Science
1. Task Board
2. Introduction
3. Python for R Users
3.11. Python dictionary
3.12. Profiling
3.13. Gamma MLE Simulation Study
3.14. Matplotlib
3.15. Advanced Matplotlib
4. Numpy
4.2. Numpy Advanced
5. Scipy
5.3. Optimization
6. Pandas
6.12. Pandas: Missing Data and Hierarchical Indexing
6.13. Pandas: Dataset Operations
7. Scikit Learn
7.1. Measures of classification accuracy and functions in Python
7.2. Fraud Detection with Python (Github Trenton McKinney)
7.3. Support vector machine
7.5. Decision Trees and Random Forest
7.6. Naive Bayes Classification Problem:
7.7. Credit Card Fraud Detection
7.8. XGBoost
7.9. Neural Networks in Python
7.10. Neural Network and Deep Learning
7.11. Recurrent Neural Network
7.13. Gradient descent
8. Data Science Competition
9. Miscellaneous learnings
Index