Compilation of Data Science Machine Learning Projects completed throughout Practicum's Data Science professional training program.
| Project name | Description | Libraries used |
|---|---|---|
| Credit Loan Analysis | Utilizing different metrics to determine the likelihood that a customer defaults on a loan. | pandas, nltk |
| Car Sales Ads | Determining the market value of car sales ads, and defining parameters that make it possible to create an automated system capable of detecting anomalies and fraud. | pandas, matplotlib.pyplot |
| Telecom Plans Analysis | Selecting the plan with the highest potential revenue for different target markets through analyzing data from different telecom packages and conducting statistical hypothesis testing. | pandas, numpy, math, scipy, functools |
| Video Game Analysis | Identifying patterns in historical game sales data, analyzing metrics for each video game platform, and conducting statistical hypothesis testing to spot potential big winners and plan advertising campaigns. | pandas, numpy, math, scipy, functools, matplotlib.pyplot |
| Telecom Plans ML Model | Developing a machine learning model using aggregated data from the Telecom Plans project to predict the most suitable plan for each customer. | pandas, sklearn |
| Bank Chruns Customers ML Model | Creating a classification model to predict customer churn for a bank from an imbalanced dataset. | pandas, sklearn, numpy |
| Oil Well ML Prediction | Analyzing data from several petroleum reservoir regions and oil wells to calculate the profitability and risk of loss of developing a new well in each region. | pandas, numpy, sklearn |
| Gold Extraction ML | Preparing a machine learning model that predicts the amount of gold recovered from the extraction process for the purpose of optimizing production and eliminating unprofitable parameters. | pandas, numpy, matplotlib.pyplot, sklearn |
| Insurance Company Data Obfuscation | Developing a data transforming algorithm for data obfuscation, and ensuring that data obfuscation does not impact the quality of a machine learning model. | pandas, sklearn, numpy |
| Car Price Model | Building a model using historical car data for an app feature that can determine the market value of a user's car. | pandas, catboost, sklearn, time, lightgbm |
| Taxi Orders Time Series ML Prediction | Utilizing historical data on taxi orders at airports to create a model that predicts the amount of taxi orders for any given time frame. | pandas, statsmodels.tsa.seasonal, matplotlib.pyplot, sklearn, lightgbm |
| NLP IMDB Review Sentiment Analysis | Training a model to automatically detect negative reviews for a system used to filter and categorize movie reviews. | math, numpy, pandas, matplotlib, seaborn, tqdm |
| Age Prediction from Photo Computer Vision | Training and evaluating a model to automatically detect the age of a customer at a checkout counter. | pandas, tensorflow, PIL, glob, numpy, matplotlib.py |
| Telecom Churns Prediction | Forecast telecom churn of clients to help marketing team. If it's discovered that a user is planning to leave, they will be offered promotional codes and special plan options. | pandas, numpy, sklearn, lightgbm |
Projects are listed in the order that they were completed.