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Data Science Foundations II | Statistics Fundamentals for Data Science | Sampling for Data Science

S7-S8 Main Project: Concatenation of Attention Enhanced Spatial and Temporal Features for Violence Detection from Videos

Perform an exploratory data analysis and provide actionable insights for a food aggregator company to get a fair idea about the demand of different restaurants and cuisines, which will help them enhance their customer experience and improve the business

Media repository to serve Sigmoid Academy, a data science learning platform with coding challenges.

Prediction of degree of obesity from anthropometric measurements. Load new data, calculate indicators for a new patient. Allow professionals to classified and label data. Application in Streamlit. API FastAPI.

Jupyter notebook, replicating studies on social capital from Nature journal, analyze economic connectedness, upward income mobility, and more. Python and relevant datasets are utilized to recreate figures and analyses.

This project features make it ideal for dynamic HR dashboards, offering insights into candidate profiles and recruitment processes.

Key features included are data preprocessing, exploratory data analysis, model training and evaluation, as well as visualization of forecasted sales trends. Whether you're a business owner, data scientist, or enthusiast, this repository provides valuable insights and tools to optimize sales strategies and enhance decision-making processes.

Conduct comprehensive Exploratory Data Analysis(EDA) for red and white wines using pandas, matplotlib, and seaborn from scratch.

IPL Fantasy Cricket Dream 11 Team Predictor is a Flask Web Application that predicts the best fantasy cricket team based on player's previous records.

Conducting exploratory data analysis on the Brooklyn99

Data Science Projects carried out during studing the DS Course by SkillFactory

Resource to help beginners in Data Science

Проекты, выполненные в рамках образовательной программы "Специалист по Data Science" АНО ДПО "Образовательные технологии Яндекса"

Predicting Bank note genuine or not.

Created a SparkML RandomForest model to predict total employee compensation. Queried data with SparkSQL, ran PySpark scripts to run EDA, pre-process data, and train model achieving with 0.98 R2 score.

Guided machine learning project for online course

The Currency Exchange Rate Prediction System is a Python application designed to assist users in analyzing historical currency exchange rates. It predicts future rates and makes recommendations on buying or selling currencies.