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audiobooks_data

The goal of this data science project is to build a machine learning model that predicts whether a customer of an audiobook app will make another purchase or not. The data includes information about the customer's past purchases, demographics, and engagement with the app.

dynamic-streamlit-data-science-project

This project aims to develop a machine learning model using different datasets dynamically and with minimal code repetition. It includes data preprocessing, model selection and evaluation, as well as the Streamlit web application for interactive exploration.

finding_excessive_absenteeism

This data science project aims to identify factors contributing to excessive absenteeism in the workplace using an absenteeism dataset. The goal is to develop a predictive model that can accurately identify employees at risk of excessive absenteeism with logistic regression ML model.

medical-cost

online_food_ordering_system

Online Food Ordering System Project Management school project. Feasibility analysis, functional and non-functional requirements, use case and stories defined. Activity and Sequence diagrams plotted. Overall we estimated whether project is applicable in real world.

pyspark-house-price-prediction

PySpark House Price Prediction features a PySpark-based Linear Regression model for predicting median house prices. It showcases data preprocessing, model training, and evaluation, yielding an RMSE of around 0.11. The code offers insights into building robust predictive models using PySpark.

reader_writer_deadlock

The readers-writers problem is used to manage synchronization so that there are no problems with the object data. Deadlock solver with no starvation used semaphore and mutex and threads.

sector-based-time-series-classification-and-similarity-analysis

Sector based classification with feature engineering and tsfresh. Looking 3 months momentum of stocks.

snake_game_reinforcement_learning

This project implements a Snake game reinforcement learning model using Deep Q-Networks with the PyTorch library in Python. The model uses a neural network to predict the optimal action-value function, which maps the state of the game to the expected future rewards for each possible action.

text_based_card_game

Turn based card game playable on console as text school project. Cards and the game mechanism inspired from Magic the Gathering game. Whole code is in single file and no external libraries required nor used.

top10_frequent_words

This is a c++ application that reads and counts unique words used in documents and sorts it by top 10 frequent used words. No explicit library used for parsing. Hashtable and selection sort used.