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algo-scriptml

Scripts of Machine Learning Algorithms from Scratch. Implementations of machine learning models and algorithms using nothing but NumPy with a focus on accessibility. Aims to cover everything from basic to advance.

arsentieva

awesome-computer-science

An awesome list of everything that exists in Computer Science and Related fields.

dishita2602

dishitaneve.github.io

dsmban

dsmban1

googlemap-business-scraper

Business directory scraper bases on google map business results

healthcheck

Health Check ✔ is a Machine Learning Web Application made using Flask that can predict mainly three diseases i.e. Diabetes, Heart Disease, and Cancer.

ipl-data-analysis

Data Analysis and Visualizations done on IPL dataset

lifemedeasy

🩺 lifeMEDeasy - Automating Healthcare and making Health facilities available to everyone regardless of their limitations⚕

ml-projectyard

This repo consists of multiple machine learning based projects with frontend

my_task1_tsf_grip_nov20_

Prediction Using Supervised Learning

my_task2_tsf_grip_nov20_

Prediction Using Unsupervised Learning

nlp-question-generation

normalization-of-company-names-for-data-management-company

on-modeling-of-covid-19-for-the-indian-subcontinent-using-polynomial-and-supervised-learning-regress

Methods used for prediction are Polynomial Regression, Support Vector Regression, Random Forest Regression, Naive Bayes Regression

on-modeling-of-covid-19-for-the-indian-subcontinent-using-supervised-learning-regression

COVID-19, a recently declared pandemic by WHO has taken the world by storm causing catastrophic damage to human life. The novel cornonavirus disease was first incepted in the Wuhan city of China on 31st December 2019. The symptoms include fever, cough, fatigue, shortness of breath or breathing difficulties, and loss of smell and taste. Since the devastating phenomenon is essentially a time-series representation, accurate modeling may benefit in identifying the root cause and accelerate the diagnosis. In the current analysis, COVID-19 modeling is done for the Indian subcontinent based on the data collected for the total cases confirmed, daily recovered, daily deaths, total recovered and total deaths. The data is treated with total confirmed cases as the target variable and rest as feature variables. It is observed that Support vector regressions yields accurate results followed by Polynomial regression. Random forest regression results in overfitting followed by poor Bayesian regression due to highly correlated feature variables. Further, in order to examine the effect of neighboring countries, Pearson correlation matrix is computed to identify geographic cause and effect.

pythondata

repo for code published on pythondata.com

pythonweek-graduateadmission

My submission for Python Week Hackathon. It is a Web app that will predict whether a user will get admission in a graduate program or not.

statistics-and-econometrics-for-data-science

This repository contains notebooks for understanding some concepts of statistics and econometrics that can be helpful in data science

thermography

Automatic detection of defected solar panel modules