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Miuul DataScience Bootcamp 2002

A collection of real-word projects on real data sets from Miuul Data Science & Machine Learning Bootcamp

1. Python Programming for Data Science

- Environment Settings
- Data Structures
- Functions
- Conditions
- Loops
- Comprehension
- Numpy and Pandas   
- Advanced Exploratory Data Analysis (EDA)

2. CRM Analytics

- CRM Analytics
- RFM Analysis
- Customer Lifetime Value
- Customer Lifetime Value Estimation

3. Measurement Problems

- Rating Products
- Sorting Products
- Sorting Reviews
- AB Testing

4. Recommendation Systems

- Association Rule Learning
- Content Based Recommendation
- Item Based Collaborative Filtering
- User Based Collaborative Filtering
- Model Based Matrix Factorization

5. Feature Engineering

- Outliers
- Missing Values
- Encoding Scaling
- Feature Extraction

Resources

  • Miuul & VBO Data Scientist Bootcamp
  • Sarkar, D., Bali, R., & Sharma, T. (2018). Practical machine learning with python. A Problem-Solvers Guide To Building Real-World Intelligent Systems. Berkely: Apress.
  • Joshi, P. (2016). Python machine learning cookbook. Packt Publishing Ltd.
  • Bruce, P., Bruce, A., & Gedeck, P. (2020). Practical statistics for data scientists: 50+ essential concepts using R and Python. O'Reilly Media.