Hey! It's Rohit Sahu and I'm a Data Science Enthusiast located in Gwalior, MP. I've created multiple projects on Machine Learning,NLP and Computer Vision.
I'm a bit of a digital product junky. Over the years, I've used hundreds of Machine Learning projects in different industries and verticals. Feel free to contact me here.
It is a predictive application that predicts the chance of getting Disease and we are providing 5 disease predictions that are Breast Cancer, Brain Stroke, Diabetes, heart failure, and kidney failure.
Tech Stack - Machine Learning, Data Analytics, Data Visualization Html, Css, JavaScript, Flask and Deployed on Heroku & Netlify
Key features - Predicting Chance of getting the disease, providing Deep information about the disease, Project is deployed on netlify and Heroku, You can use it.
Case Study
Marking Attendance with the help of Camera by face detection and Providing a dashboard that shows Retention metrics of users.
Tech Stack - Opencv , Face Recognition , Data Analytics , PHP , Streamlit,Flask ,MySQL and Deployed on Heroku & InfinityFree.
Key features - Automatic Attendance Marking, providing a Dashboard, Attendance management System.
Case Study
To Know how much Current Notifications are on the job when we will use the Data Keyword.
Tech Stack - Data Extraction, Data Mining, Exploratory Data Analysis, Data Profiling, Data Cleansing, Feature engineering, Data Preprocessing, Data Visualization.
Key features - Finding New vacancies in Naukri.com based on the Data Keyword and company wants how many job Skills for the job.
Case Study
It is an Application that predicts the chance of getting a brain stroke and provides the information.
Tech Stack - Machine Learning, Data Analysis, Html, CSS, JavaScript, Flask and Deployed on Heroku & Netlify.
Key features - Predicting whether a patient has a stroke or not using thier data.
Case Study
In this Project, we are taking different datasets and performing EDA, Prediction, Data Analysis, visualization, and many more.
Tech Stack - EDA, Descriptive stat., Prescriptive stat., data cleaning, data Preprocessing, feature engg., feature selection, model training.
Key features -focusing on accuracy, practice with hypertunning, and practice with a different library.
Case Study
