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Stars1
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LanguageJupyter Notebook
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Created almost 5 years ago
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Updated over 4 years ago
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COVID-19-Forecasting
COVID19 forecasting country wise for cumilitive confirmed cases and fatalities. ML Algorithms: Various regression algorithms such as Ridge, Lasso with Polynomial Feature, Random Forest, XGboost, LightGBM, FbProphet etc.Mathematics-for-Machine-Learning-Specialization
Mathematics for Machine Learning Specialization from Imperial College London on Coursera_AssignmentsSite-Down-Prediction
Predictive analysis using machine learning algorithms to forecast future site down based on historical data. Initially single feature linear regression used to build the model. The popular time series used as feature in linear regression with necessary hyper-parameter tuning. Some good and promising result achieved after running the model with very high accuracy in some of the cases. In future have a plan to further improve the model with more features and high training data.Pump-it-Up
Using data from Taarifa and the Tanzanian Ministry of Water, Predict which pumps are functional, which need some repairs, and which don't work at all using classification algorithms while maximizing the classification rate (0.81 score achieved). It is a competition on drivendata.org.COVID-19-Dashboard
An Interactive visualization in Tableau to show total & new confirmed cases, fatalities, recovery *countrywise trend analysis *countrywise comparison in bar charts *geographical heat map with option to filter by country *additional filter option to select multiple countries to compare. https://public.tableau.com/profile/md.mahmud.ferdous#!/vizhome/COVID-19Dashboard_15846933692270/DashboardLove Open Source and this site? Check out how you can help us
