SAURABH BUDHWANI

[ adm3g9@r.postjobfree.com Ó +91-999******* Vadodara, Gujarat, India Saurabh-Budhwani CERTIFICATIONS

Introduction to Data Science - Coursera

Certificate-link

Applied Plotting, Charting Data Represen-

tation in Python - Coursera

Certificate-link

Intermediate Machine Learning - Kaggle

Certificate-link

Advanced SQL - Kaggle

Certificate-link

Data Cleaning - Kaggle

Certificate-link

Feature Engineering - Kaggle

Certificate-link

Learning Data Analysis(NASBA) - Linkedin

Learning

Certificate-link

SQL Essentials Training - Linkedin Learning

Certificate-link

EXPERIENCE

Graduate Engineer Trainee

Welspun Corp Ltd., Anjar, Gujarat

August, 2020 – Present

• Currently working in Automation Department.

Working on automation projects for removing

manual interventions in and helping increase

production speed.

Research Intern

National Institute of Technology, Surat

JUNE 2019 – JULY 2019

• Internship on Simultaneous Localization And

Mapping (SLAM) On a differential drive Robot,

here I trained the te robot with the help of

Robotics Operating system(ROS) which used

K-means algorithm to make the robot learn its

environment and make map out of it.

LEADERSHIP ROLES

• Managerial coordinator at techno-cultural fest

2017 2018 (NIT,Surat).

HOBBIES

• Table Tennis, Football, Reading.

SKILLS

Programming

Python, C, SQL, Data Analysis, Machine Learning.

Library

Numpy, Pandas, Matplotlib, Seaborn, Scikit-Learn, XG- Boost, Reguler Experssion(Novice)

Databases

Ms SQL Server, MYSQLi, SQLite,

Computer Software

GitHub,Tableau, Ms EXCEL, Matlab.

EDUCATION

Bachelor of Technology (Electrical Engineering)

National Institute of Technology, SURAT

August, 2016 – June, 2020

• CGPA - 6.51

PROJECTS

Data Analysis on Covid19 Data

• Used Ms SQL Server to do Exploratory data analysis on covid dataset

• Made data visualizations using Tableau with the help of data generated using SQL queries. - Project-link

Exploratory data analysis on Facebook dataset

• Used pandas, numpy and Seaborn on jupyer notebook, to do Exploratory data analysis on Facebook dataset. - Project-link End-to-End used car price estimation using Machine Learning

• The main goal of this end-to-end project was to predict prices of used cars using vehicle data for Kaggle dataset using Su- pervised learning by using features to train the model.The first thing to do was data cleaning, the some Exploratory Data Analysis using matplotlib and seaborn.Calculating Feature Im- portance using ExtraTreesRegressor . Then hyperparameter- ing for the model training and then selecting best parameters using RandomizedSearchCV, then training the model using RandomForestRegressor .Validating the model using distplot and scatterplot, then using pickle to dump the model.Then us- ing flask to make an HMI and finally dumping it using heroku app by deploying through github. - Project-link

Real-Estate price estimation using Machine Learning

• Predict Real-Estate prices using Supervised learning by using features to train the model.

• Data cleaning, then some Exploratory Data Analysis matplotlib and seaborn.

• Created new correlations, forming a pipeline for imputing and standardising values

• Use of RandomForestRegressor model for training

• Cross-validation of the trained model

• At last using joblib for dumping and loading the trained model so it can be further used.

• mean squared error for validation of the model. - Project-link

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