| 01 - Exploratory Data Analysis |
📊 Analysis of apartment sale advertisements |
- Analyze data from Yandex Real Estate to determine the market value of real estate objects in St. Petersburg and surrounding areas. |
matplotlib, pandas, numpy |
| 02 - Statistical Data Analysis |
📊 Statistical data analysis |
- Analyze user data from a scooter rental service to test hypotheses aimed at increasing business profitability. |
math, matplotlib, numpy, pandas, scipy |
| 03 - Identifying Product Success Factors |
📈 Identifying product success factors |
- Identify patterns in historical sales data, user ratings, and platform genres to determine factors that contribute to game success. |
matplotlib, numpy, seaborn, pandas, scipy |
| 04 - Linear Models in ML |
📈 Linear models in machine learning |
- Develop a machine learning model to manage risks and facilitate objective purchasing decisions. |
matplotlib, numpy, seaborn, pandas, scipy, phik, sklearn |
| 05 - Supervised Learning: Model Quality |
📈 Supervised learning: model quality |
- Create a personalized offer solution for regular customers to enhance their purchasing activity. |
matplotlib, numpy, seaborn, pandas, scipy, phik, sklearn, shap, pipeline |
| 06 - Job Satisfaction and Attrition Forecasting |
🏢 Capstone Project #2: Job Satisfaction and Attrition Forecasting |
- Build models to predict employee satisfaction and attrition based on customer data. |
matplotlib, numpy, seaborn, pandas, scipy, phik, sklearn, pipeline |
| 07 - Machine Learning in Business |
🏢 Machine learning in business |
- Develop a model to identify regions for profitable extraction and analyze potential profits and risks using Bootstrap techniques. |
matplotlib, numpy, seaborn, pandas, scipy, phik, sklearn, pipeline |
| 08 - Numerical Methods |
📊 Numerical methods |
- Create a model to determine car prices based on technical specifications and configurations. |
matplotlib, numpy, seaborn, pandas, scipy, phik, sklearn, pipeline, time, catboost, lightgbm |
| 09 - Time Series |
📈 Time series forecasting |
- Forecast the number of taxi orders at airports to optimize driver availability during peak hours. |
os, matplotlib, numpy, statsmodels.tsa, pandas, RandomizedSearchCV, sklearn, pipeline, time, TimeSeriesSplit, DecisionTreeRegressor, lightgbm |
| 10 - Machine Learning for Texts |
📊 Machine learning for texts |
- Develop a tool to identify toxic comments in product descriptions for moderation in the online store "WikiShop". |
os, matplotlib, numpy, nltk, pandas, RandomizedSearchCV, sklearn, pipeline, tqdm, wordcloud, lightgbm |
| 11 - Computer Vision: Neural Network Training Practice |
🧠 Computer vision: neural network training practice |
- Train a neural network for age recognition based on photographs. |
seaborn, keras, pandas |
| 12 - Capstone Project |
🚀 Capstone project |
- Develop a comprehensive solution integrating various data science techniques. |
TBD |