Rohit Kumar

adm178@r.postjobfree.com

+91-887*******

Ranchi, India

linkedin.com/in/rohit-kumar-3543b31b0

EXPERIENCE

Volunteer Aug 2019 - Aug 2019

Amity University Jharkhand Ranchi, India

In university festival I did a volunteer job to successfully complete the net-ball competition. In this competition various colleges and university students are present and we have to manage the time and the score as well as the aggression of the players. Coordinator Sep 2019 - Sep 2019

Department Event Ranchi, India

I am the coordinator and president of the Natural Help Group in my Department at university. In this department we did a plantation in Doranda river side. I take the responsibility and review the side of plantation before the plantation day, I find the way to go to the plantation side for others and also at plantation day I take the chief guest and my university vice chancellor to the plantation site. EDUCATION

Master’s Degree, Computer Applications 2021

Amity University India

Currently I am doing my Masters of Computer Science at Amity University Jharkhand and I am also studying Machine Learning by myself. My field of interest is Machine Learning and Data Science.

Bachelor’s Degree, Computer Applications 2018

Birla Institute of Technology Ranchi, India

I have completed my Bachelors of Computer Science from Birla Institute of Technology Lalpur Ranchi with first class. SKILLS LANGUAGES

English Conversational

OTHER SKILLS & CERTIFICTIONS

Certificate of Recognition by Here Technologies – Map Expert Certificate of completion by Julia Academy – Introduction of Julia Certificate of Programming Essential in Python – Python Institute (Open Education & Development Group) Machine Learning for Everyone Track – Datacamp

Machine Learning Scientist with Python Track – Datacamp Internship:

Certificate of Internship Completion on Machine Learning by – MedTourEasy In this internship I build a model which can detect the American sign language sign A,B and C by looking at the hand sign. Projects:

Tuberculosis detection – using Keras Sequential model to detect the tuberculosis using chest X-rays, used sequential model because it produce binary output which is very good for this project. The projects precision, recall and f1-score is above 90%, which is very good for data size of 7000 x-rays images. Basics_NLP – In this basic project name "Basics_NLP" I try to detect spam messages where "0" represent non spam message and "1" represent spam message. I use accuracy, precision, and recall to check the performance of my model. It give very high scores in all of the matrics. I also check my model with examples for both spam and non-spam. I used TfidfVectoriser and LogistictRegressor to build the model and train the model. Stroke Prediction – in this project I used keras Sequential model to detect the chances of stroke this models’ validation accuracy is above 95%. HR_analysis – This project model will tell the HR that how much chance is there that any one of his/her employee left the job. In this I used Support vector machine algorithm to detect the probability.

Diabetes detection – In this project I use support vector machine and KNeighbors Classifier to predict that any person have diabetes or not. Its precision is around 80 and 70 and recall is around 85 and 70 also the f1-score is around 85 and 70. Note-Data – In this project I try to predict genuine and forged banknote using Keras Sequential model up to 500 epochs its validation accuracy is above 98% and classification report is also near to 1 for every parameter. Heart-Failure – In this project I try to predict the chance of heart failure of any person in this project I used CNN, XGBoostClassifier, K Neighbors Classifier and Support Vector Mahine Algorithms. Classification report for SVM is around 80 and 55, for XGBoost it is near about 85 and 55 to 60, for KNN it is near about 80 and 40 and for sequential model it is near about 85 and 65. TensorFlow Other Languages

HTML Weka R Python SPSS SQL

Julia Keras

Bike_ride_prediction – In this project I try to predict the number of bikes which will use to take ride on any specific day. For building this model I used various ML algorithms like Linear Regressor, DecisionTree Regressor, RandomForest Regressor, XGBRegressor. For checking model performance I use MSE and r2- score.

Project link – https://www.kaggle.com/rohitkumar2396/basic-nlp https://www.kaggle.com/rohitkumar2396/stroke-prediction https://www.kaggle.com/rohitkumar2396/hr-analysis

https://www.kaggle.com/rohitkumar2396/diabetes-dataset https://www.kaggle.com/rohitkumar2396/bank-note

https://www.kaggle.com/rohitkumar2396/heart-failure Github link - https://github.com/RohitKumar23-11