Visualization and Imputation of Missing Values

Automated Tool for Optimized Modelling

Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

A proof-of-concept on how to install and use Torchserve in various mode

Graphical user interface for designing and simulating model predictive control using MATLAB and the Multi-Parametric Toolbox 3

🧬Protein Functions Prediction through Amino Acids Sequences🧬

Cadivascular Disease Prediction

Credit card fraud detection-prediction model

This repo evaluates Logistic Regression, Random Forest, and Support Vector Machine models for predicting stroke risk. Implemented in Python, the project includes data pre-processing, model training, and performance metric calculations

This repo contains python scripts that are needed to deploy a machine learning model behind gRPC running using asyncio.

This repo contains a python script which is a fastapi backend server that can be used for model (Image classification) predictions

Customer lifetime value predictions

Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

This Project analyses the carbon footprint of the U.S. commercial sector using three machine learning models. A combination of energy consumption data and carbon dioxide emission data was used to achieve the carbon footprint variable.

Used libraries and functions as follows:

Red wine quality prediction machine learning model.

Final project for the IBM for Data Analysis module. Statistical analysis and Model Evaluation with Python using Seattle housing data

Contains Data related content with R