Resume

Education

Full Stack Data Science Bootcamp

2022 - 2023

iNeuron.ai, Bengaluru

B.Tech in Electronics & Communication Engineering

2011 - 2014

Gujarat Institute of Technical Studies, Moyad, Gujarat

Completed my B.Tech (EC) degree with a Cumulative Grade Point Average (CGPA) of 8.14 [Certificate]

Diploma in Electronics & Communication Engineering

2008 - 2011

Lakhdhirji Engineering College, Morbi, Gujarat

Complete my Diploma (EC) with Cumulative Performance Index (CPI) of 7.82 [Certificate]

Certifications

Full Stack Data Science Bootcamp

1 Jul 2023

Ineuron
Credential Id: b3e3997a-7085-4998-93d6-7fe00011867f [Show Credentials]

Deep Learning Foundation

19 Jun 2023

Ineuron
Credential Id: 93a530cb-f9e3-4ebe-8da9-addca90b9de1 [Show Credentials]

SQL Basic

21 Jun 2023

HackerRank
Credential Id: f1a7a3b4774e [Show Credentials]

Data Science Hackathon

12 Nov 2022

The Hackathon was organised by Deets Digital Pvt Ltd at IIM Ahmedabad. The problem statement was to predict the future defaulter based on bank credit card records. [Certificate]

Internship

Data Scientist

May 2022 - Present

Ineuron.ai, Bengaluru

    In ineuron.ai, I learned how data science industry works. learned python, Statistics, MongoDB, Mysql, Machine Learning, learned how supervised, unsupervised learning and clustering algorithms works and the mathemathical intuition behind them, Learned to do prediction using Machine Learning Algorithms and made rest api using flask frame work

    Projects i have worked on :

    Content Based Movie Recommendation System

  • Gathered 4803 Movies dataset from TMBD. Extracted genres, keywords, cast (Top 3 actors) and crew and include all these to Tags Feature.
  • For Text Vectorisation we have used CountVectorizer. Perform stemming using PorterStemmer, so that the words will not repeat in tags
  • Find the distance between all vectors of all movies using cosine_similarity. and Top 5 movies having lower distance are recommended.
  • Used Streamlit to create web app and deployment.

    • Predict Student Performance using ML Algorithms

  • The problem statement was to predict how much the student's performance (test scores) is affected by the given attributes.
  • First i had performed complete EDA,each and every possible visualization using matplotlib and seaborn in Jupyter Notebook
  • Modular coding in python is done to made this project and used logging and exception handling where required.
  • In Data Ingestion, imported data from MongoDB, in Data Transformation, used OneHotEncoder to encode the categorical data, and seperated the train and test datasets
  • In ModelTrainer, performed Hyperparameter tunning on different Regression algorithms and store the r2_square of the best model
  • Finally, deploy the project by creating web app using Streamlit.

    • Rental Bike Share Prediction using Supervised Learning ML Algorithms

  • The Bike Share Prediction helps companies to predict how many counts of bikes will be required on that particular day based on some input data
  • Modular coding in python is done to made this project and used logging and exception handling where required.
  • Imported data from MongoDB in DataIngestion, then do DataValidation, Data Transformation, ModelTraining, Model Evaluation, Model Pusher and store the output pickle files in artifact folder
  • Deployed the project by creating web app using Streamlit.
  • Created Technical documentation such as : Architecture Design | Detailed Project Report | HLD | LLD | Wireframe

    • Predict APS Failure at Scania Trucks using ML Algorithms

  • Used dataset having readings of 171 sensors.
  • After EDA, Preprocessing, Feature Selection and Handling the outliers, We seperated dependent and independent features.
  • For Model Building i have used different classifiers as this was a classification problem statement and finds that XG Boost gives highest accuracy of 99%
  • To be absolutely sure and to avoid model from over-fitting, i have done Hyperparameter tunning using GridSearchCV and again the accuracy of XGBoost Classifier was maximum (99%)

    • Predict the car price and build Flask Web App for Deployment

  • Used dataset from kaggle having 892 records and 6 features.
  • The data has many categorical features so we have used OneHotEncoder for encoding all features.
  • For model building we have used linear regession but at first our r2_score was very less 57%, so we run a for loop of 1-1000 to check r2_score for different values of random_state. and finds that at random_state 433 r2_score id max 84%
  • We store the model in pickle file and made Flask web app for deployment in Heroku

    • Web Scrapping Using Python

  • Scrapped https://github.com/topics
    - Used requests to download the page
    - Used BeautifulSoup from BS4 to parse and extract information
  • For each topics, extracted Topic Title, Topic Page URL, and Topic Description
  • For each topics, extracted Top 20 repositories.
  • For each repository, graped the Repo name, username, stars, and repo URL
  • Converted the extracted information into a pandas dataframe and for each topic, created a CSV file.

Professional Experience

Ex Business Owner

2014 - 2022

MG Engineering, Kadi, Gujarat

  • Create business plans, arrange financing, hire staff, review sales, develop marketing strategies, oversee daily activity, and identify business opportunitites.
  • Do continous research of new materials that can be used to manufacture Tiles.
  • Do line trails of existing products in different companies (part of B2B marketing).
  • Satisfactorily handling a team of 6-7 workers and 4-5 marketing technicians.
  • Ensure that equipments and machinery are adequately maintained and promptly repaired by assigned workers.

Freelance Editor Experience

Freelancer Editor

2020 - Present

Freelancer

  • 3 years of experience as a video editor with a proven track record of creating high-quality video content for various clients.
  • Worked with clients to understand their video needs and created content that met their goals and exceeded their expectations.
  • Collaborated with other team members to ensure that videos were completed on time and within budget
  • Editing online freelancing projects from upwork and other freelancing websites. Maintained 90% Job Completion rate on upwork.
  • Managing youtube channel of INNOFIED, a kolkata based startup.

Video Editor & Motion Graphics Designer

2019 - 2020

V3 Production, Ahmedabad, Gujarat

  • Performed post-production work, including, assembling raw footage, Editing, sound and sequences and providing final film within time and budget constraints.
  • Have done many outdoor projects including aarambh event, held at tent city, statue of unity where our honourable PM Shri Narendra Modi was Chief Guest.
  • Edited Interviews, Logo Animations, Infographics Videos and Corporate Films.

Video Editor

Jan 2019 - Apr 2019

Ansh Production, Ahmedabad, Gujarat

  • Editing educational videos for Gujarat University.