Python Programming for Data Science
- Python Exercises
- List Comprehensions and Pandas Exercises
- Lead Calculation with Rule-Based Classification
- Advanced Exploratory Data Analysis and Data Visualization using Netflix Dataset
Customer Relationship Management (CRM) Analysis
- Recency (R), Frequency (F) and Monetary (M) Segmentation of Customers using Online Retail Dataset
- Customer Lifetime Value (CLTV) Calculation using Online Retail Dataset
- Customer Lifetime Value (CLTV) Prediction with BG-NBD and Gamma Gamma Models using Online Retail Dataset
- Customer Lifetime Value (CLTV) Prediction with the models BG-NBD and Gamma-Gamma – FLO Example
- Customer Segmentation using RFM and KMeans Methods and Association Rule Analysis – Online Retail Example
- Customer Segmentation with RFM and KMeans – FLO Example
Measurement Problems
- Scoring and sorting the IMDB Top250 Lists
- Comparing Conversion of Bidding Methods with AB Testing
- Rating products and sorting reviews in amazon
- Sorting reviews using the data collected from an e-commerce company
- An application for calculating the product rating over the ratings given to a product
Recommendation Systems
- Developing an ARL Based Recommender System using the Dataset Online Retail
- Developing a Hybrid Recommender System
- Developing a Prediction-Based Recommendation System using Model-Based Matrix Factorization
- Developing a User-Based Recommendation System using the Datasets ‘Movie and Rating’
- Item-Based Recommendation System using the Datasets ‘Movie and Rating’
- ARL Recommender System using the Armut Data
- Association Rule Learning using the Dataset Online Retail II
- Developing a Content-Based Recommendation System using Metadata of Movies
Feature Engineering and Machine Learning
- House Price Prediction using PyCaret
- Classification of Talent Hunting using PyCaret
- Classification of Talent Hunting with Artificial Learning
- Customer Segmentation with Unsupervised Machine Learning Models
- Developing Machine Learning Models to Predict House Price
- Exploratory Data Analysis, Feature Engineering, and Developing a Machine Learning Model to Prevent Telco Customer Churn
- Error Evaluation for Regression Models
- Estimating CO2 Emissions using Linear Regression and Lazy Regression
- Prediction of CO2 Emissions using Linear Regression, Polynomial Regression, KNN, and Lazy Regressor
- Analysis of China Gross Domestic Product (GDP)
- Hierarchical Clustering Analysis of US Arrests
- Diabetes Prediction using Basic Modeling