Pinned Repositories
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
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.
Deploy-Your-First-Machine-Learning-Model
flu-shot-learning
Predict H1N1 and Seasonal Flu Vaccines with ML Algorithms
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.
Python-for-Financial-Analysis-and-Algorithmic-Trading
python, pandas, time series analysis, algorithmic trading, financial analysis, matplotlib, data visualization
Slashing-Prices-for-the-Biggest-Sale-Day
akshit113's Repositories
akshit113/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.
akshit113/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.
akshit113/advent-of-code-solutions
Solutions to https://adventofcode.com/2018
akshit113/Blueberry-Yield-Prediction
Predict bueberry yield from 18 input features
akshit113/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.
akshit113/Deploy-Your-First-Machine-Learning-Model
akshit113/flu-shot-learning
Predict H1N1 and Seasonal Flu Vaccines with ML Algorithms
akshit113/Python-for-Financial-Analysis-and-Algorithmic-Trading
python, pandas, time series analysis, algorithmic trading, financial analysis, matplotlib, data visualization
akshit113/Slashing-Prices-for-the-Biggest-Sale-Day
akshit113/Car-Price-Prediction
akshit113/demo_dbt
Repository to learn dbt
akshit113/docs
TensorFlow documentation
akshit113/Edabit-Python-Classes
akshit113/flask-application
akshit113/gitignore
A collection of useful .gitignore templates
akshit113/HackerRank-Practice-Problems
This repository contains solutions to hackerrank problems
akshit113/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.
akshit113/hudson-river-test
akshit113/IMDB-Movie-Reviews-Sentiment-Analysis-Using-LSTM-Networks
The project performs binary sentiment classification (positive or negative) on IMDB Movie Reviews dataset
akshit113/Julia-Programming-With-MAchine-Learning
akshit113/Leetcode-problems
akshit113/machine-learning-code-snippets
akshit113/movie-reviews-sentiment-analysis
Performs sentiment analysis of movie reviews and classifies each review as positive and negative
akshit113/Predict-Heart-Failures-with-Clinical-Features-Using-Machine-Learning-Algorithms
akshit113/predicting-bank-marketing-campaign-success
akshit113/predicting-hit-songs_on_spotify_using_ANNs
performs binary classification using sequential keras model using selu activation function
akshit113/Spotify-API-Endpoints
akshit113/t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
akshit113/test_bank_notes_authentication_fastAPI-Heroku
akshit113/testing-git-through-git-bash
testing git bash