Stock Market Price Prediction: Used machine learning algorithms such as Linear Regression, Logistics Regression, Naive Bayes, K Nearest Neighbor, Support Vector Machine, Decision Tree, and Random Forest to identify which algorithm gives better results. Used Neural Networks such as Auto ARIMA, Prophet(Time-Series), and LSTM(Long Term-Short Memory…

Exploring of Diverse Plant Communities and Adaptation to Drought Conditions Based on Advanced Logistics Model with Variable Growth

Credit card Fraud Transaction Detection using various machine learning algorithm.

Applying different algorithms (RandomForest, K-NearestNeighbors and LogisticRegression) to predict target and compare their results.

Project for predicting Heart_Disease using Logistics Regression

Create, deploy and interact with a Machine Learning model in real time. Project involves training a Logistics Regression model for a binary classification task and deploying the trained model in a webserver to obtain real-time predictions via rest API using a simple web page

Investigating Population Diversity, Sex Ratio Dynamics, and Resource Utilization: Insights into Lamprey Species within the Multispecies Ecosystem of the Great Lakes

Participate in a Kaggle-like machine learning competition and submit the model's predictions to your teacher/TA to be evaluated in an independent way

Survival probability of burn injury patients based on age, sex, race, hospital facility, and other significant facility nearing respondents.

Bank Customer Chun Rate

Delinquency Model to predict the loan repayment using Machine Learning. Visit https://yesdeepakmittal.github.io/delinquencymodel/

Analyzed the effectiveness of COVID vaccine on 8 different age groups and trained 5 classification machine learning models to check whether the the vaccine developed immunity in 100k people from an age group or not.

Python Pandas Program That Predicts Passengers That Survived The Titanic Sinking

Efficient Modeling and Prediction of E-commerce Recommendation System: A Case Study on Amazon-Product Review Dataset

Data analysis project on an e-mail database using Python

Using labelled classifed data to infer a learning algorithm in R

A program which determines if there is chance that you can be admitted in a University using Logistics Regression

The following is one of the assignments for the Data Mining class that I took on the 6th semester. I was assigned to classify sanitation data in Surabaya using Logistics Regression, Decision Tree, Naive Bayes, K-Nearest Neighbor, and Support Vector Machine.

Applying different algorithms (RandomForest, K-NearestNeighbors and LogisticRegression) to predict Attrition for a fictional company.