akshit113 Goto Github PK

accessing-zomato-api-endpoints-with-python

Hitting Zomato API Endpoints at https://developers.zomato.com/documentation

advent-of-code-solutions

Solutions to https://adventofcode.com/2018

anemia-diagnosis

This data set presents the prevalence of different types of Anemia including it’s severity and association with age and gender of the study population with CBC data set parameters as variables. We generated dataset from complete blood count test performed by Hematology analyzer to determine the prevalence of different types of Anemia treated at the Eureka diagnostic center in Lucknow, India. All the procedures for the CBC test were done following standard operating protocols defined for the Hematology analyzer. For CBC investigation, 400 patient samples were randomly selected to compute the dataset from the patients who visited the Eureka diagnostic center in Lucknow for various clinical examinations. The diagnostic center performs 4 – 8CBC investigations a day on average. During the data collection period between September 2020 to December 2020, 1000 CBC investigations were performed, out of which 400 random samples were selected. We included adult males and females who are not pregnant and older than 15 years of age in the study population. Infants, young children less than 10 years old and pregnant women were excluded from the study due to various factors like variable CBC test values and other factors. After excluding the above stated persons from the randomly chosen sample of 400 patients, we were left with 364 patients in the final data set.

blueberry-yield-prediction

Predict bueberry yield from 18 input features

capstone-project

car-price-prediction

credit-risk-modeling-with-machine-learning

Banks play a crucial role in market economies. They decide who can get finance and on what terms and can make or break investment decisions. For markets and society to function, individuals and companies need access to credit. Credit scoring algorithms, which make a guess at the probability of default, are the method banks use to determine whether or not a loan should be granted. This competition requires participants to improve on the state of the art in credit scoring, by predicting the probability that somebody will experience financial distress in the next two years. The goal of this competition is to build a model that borrowers can use to help make the best financial decisions.

datasciencecoursera

Data Science Repo and blog for John Hopkins Coursera Courses. Please let me know if you have any questions.

demo_dbt

Repository to learn dbt

deploy-your-first-machine-learning-model

docs

TensorFlow documentation

edabit-python-classes

endpoints

Accessing Endpoints through various APIs in Python

flask-application

flu-shot-learning

Predict H1N1 and Seasonal Flu Vaccines with ML Algorithms

forecasting-blood-donations-in-china

gitignore

A collection of useful .gitignore templates

hackerrank-practice-problems

This repository contains solutions to hackerrank problems

heart-stroke-prediction

According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible for approximately 11% of total deaths. This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, various diseases, and smoking status. Each row in the data provides relavant information about the patient.

hudson-river-test

imdb-movie-reviews-sentiment-analysis-using-lstm-networks

The project performs binary sentiment classification (positive or negative) on IMDB Movie Reviews dataset

julia-programming-with-machine-learning

keras

Deep Learning for humans

leetcode-problems

loan_prediction_using_baseline_keras_model

predicts whether or no Loan will be approved based on factors such as gender, education, marital status, income, credit score and so on.

machine-learning-code-snippets

movie-reviews-sentiment-analysis

Performs sentiment analysis of movie reviews and classifies each review as positive and negative

multiclass-classification-using-extreme-gradient-boosting

patient-classification-through-fetal-heart-rate-with-random-forests

predict-heart-failures-with-clinical-features-using-machine-learning-algorithms