Machine Learning

Project description Language: Python Working file: Jupyter Notebook Project type: Reinforcement Learning Problem Statement Dynamic pricing is a fundamental problem in economics and operations research. Sellers repeatedly interact with customers whose willingness-to-pay is uncertain. Each round: The seller offers a price from a feasible set (1–100). The customer either accepts or rejects. The seller observes only binary feedback (buy/no-buy). In our environment: Segment Valuation Market share 1 18 0.4 2 43 0.3 3 56 0.2 4 81 0.1 The theoretical optimal price is 43, yielding the maximum expected revenue given the mixture of valuations and probabilities. ...

The objective of this project is to conduct a comprehensive analysis of Scottish schools in order to derive valuable insights. The analysis includes clustering and descriptive analysis, taking into account factors such as deprivation rate and total number of pupils. Additionally, an interactive map of Scotland has been developed to visually represent the location of each school. The clustering model has categorized local authorities into three distinct clusters based on average pupil count and deprivation score. The map highlights areas predominantly occupied by schools facing high levels of deprivation. The aim is to assist charities or non-governmental organizations (NGOs) involved in projects supporting these school pupils. All data used in this analysis is publicly available and sourced from the Scottish Government website. The Postcodes.io API was utilized to gather latitude and longitude coordinates for each school based on their respective postcodes. The codes for clustering, visualizations, map generation, and API application can be found in my GitHub repository. You are welcome to access and utilize the repository’s contents for personal or commercial purposes without seeking my consent. I hope you find this information enlightening and enjoyable to read. ...

This project is carried out by me independently. The dataset is obtained publicly from Kaggle. All codes and their explanations are stored in my GitHub repository. Project description Language: Python Libraries: sklearn, pandas, numpy, matplotlib, seaborn IDE: Jupyter notebook Project type: Machine learning, Unsupervised learning, K-Means clustering FIFA 23 is a football video game created by Electronic Arts (EA). It became the best-selling football video game in Christmas UK retail charts. According to EA statistics, the game contains more than 700 teams with over 19,000 football players, playing in at least 30 football leagues. The data used in this project is taken from Kaggle. The objective of this project is to classify the players into various segments. ...