arshmodak Goto Github PK

a-study-of-recommender-systems

datasets

A collection of datasets of ML problem solving

hurricane-wind-speed-prediction-using-deep-learning-and-machine-learning

hymn

Music Player application (Mobile Computing Assignment)

image-classification-of-225-aves-species

In-progress project where we use various Deep Learning and Machine Learning models to classify 225 birds species.

jcdb

JCDB is a windows desktop application to upload, search, sort and download research papers (Journals and Conferences) as well as student papers. This application provides a simple interface to access and upload your papers. Several filters such as title, affiliation, indexing, issue, volume, year of publication etc. can be used to pin point and access exactly which paper you want. This application can also be used to create an excel or pdf file which contains the list og papers and their details. A list is prepared depending on the attributes the user has chosen to be displayed. The target of the project is ease of use and easy maintenance of multitudinous papers under one roof. The application is coded using C#.NET along with the use of a MySQL Server. It is presented to and approved by the Research & Development Department of my college (BVDUCOEP).

loan-defaulters-eda-and-prediction-using-ml

Predicting Loan Defaulters using various Classification Algorithms using Python (Numpy, Pandas, Sklearn, Matplotlib, Seabon)

machine-learning-and-data-science

This repository consists of hard-coded machine learning algorithms (supervised learning) and a comparison to the algorithms provided by the Scikit-Learn Package in Python.

mini-ml-and-ds-projects

This Repository Contains Small Data Science and Machine Learning Projects

nih_chest_xrays_disease_detection

predicting-income-class-using-machine-learning

Predicting Income (<=50 or >50) using Machine Learning on Adult Data: =========================================================================== The adult data set consists of various features such as age, sex, education, occupation, relationship status, race etc. Using these features, I have predicted if an individuals income is either <=50k or >50. Utilizing libraries such as numpy, pandas, sklearn etc, I created various machine learning models to predict income. I also took care of imputing missing values, feature elimination, label encoding and standardization of data for the process. Metrics such as Precision, Recall, F1-Score, Accuracy, True Positive Rate, False Positive Rate and ROC were used to evaluate the model. Primarily I used Logistic Regression to predict the income, then I utilized various techniques to improve my model. They are as follows: 1. I manually selected a 0/1 classifier threshold by checking type 1 and type 2 errors 2. Implemented k-fold cross validation to reduce bias in the models. 3. Implemented Recursive Feature Elimination 4. Uni-variate Feature Elimination using "Select K Best"

predicting-nba-player-salaries-and-position-using-machine-learning

NBA is the men’s professional basketball league in North America, composed of 30 teams that compete with each other to win the Larry O’Brien Championship Trophy – previously known as Walter A. Brown Trophy. Our data set consists of data from 1996 to 2020, for all seasons and all 30 teams. A team has a maximum of 12 players. We have scraped three data sets according to three different positions of a player: Forward, Center and Guard. All three data sets have information on all the stats of the players such as player name, team name, points per game, rebounds per game, no. of wins, losses etc. We aim to find relations between various player stats and use them to predict which of the three positions a player is best suitable to play in. Furthermore, we also want to predict the efficiency of a player and their salary according to their performance in the games over time.

research-papers

Contains Published Research Papers

the-pacman-projects

This repository contains the solutions to The Pacman Projects by Berkley (CS 188). These solutions are implementations of various AI algorithms to solve various problems (essentially making AI play Pacman).