DataScientist

Vinay Kalmoodkar

Mobile No: +91-897******* / +91-789******* LinkedIn: www.linkedin.com/in/Vinay-Kalmoodkar

E-Mail: *****************@*****.*** GitHub: https://github.com/Vinay-Kalmoodkar

PROFILE SUMMARY:

•Achievement-driven professional with an experience of nearly 2 years in Python programming, Javascript and Lua.

•Experience of Machine learning algorithms like Linear and Logistic Regression, KNN, Support Vector Machines(SVM), Decision trees, Random Forest, Adaptive Boosting (ADABoost), Gradient Boosting, XGBoost and K-Means Clustering.

•Skilled in libraries like Numpy, Pandas, Matplotlib, Seaborn, Scikit Learn, Tensorflow, Keras and OpenCV.

•Strong Mathematical foundation and good in Statistics.

•Feature engineering in Python – Missing value treatment and outlier handling, transforming variables and reshaping data using Python packages like Numpy, Pandas and Scikit Learn.

•Good knowledge of Deep Learning(DL) and ample hands-on with Neural Networks, Artificial Neural Networks(ANN), Convolutional Neural Networks(CNN) and Recurrent Neural Networks(RNN).

•Basic Understanding of Computer Vision techniques like Image pre-processing, Image Segmentation, Object detection, Object recognition etc.

•Basic Understanding of Natural Language Processing (NLP) techniques like tokenization, stemming, lemmatization and word2vec.

•Self-motivated team player with good communication and presentation skills.

•Corporate Training Experience for more than 5 months.

EDUCATION QUALIFICATION:

Year

Degree

Institution

University

CGPA / Percentage

2017

B.E

PDA college of Engineering

Autonomous affiliated under VTU

9.01

2013

PUC-II

Shree Guru Independent PU college

Karnataka State Board

82

2011

SSLC

Maharishi Vidya Mandir

Karnataka State Board

90.88

TECHNICAL SKILLS:

Programming Skills

Python, Javascript, Lua, Core Java, MySQL, Node.js (basics) and MongoDB

Libraries and Softwares

Numpy, Pandas, SkLearn, Tensorflow, Keras, OpenCV, Haar Cascade, Anaconda, Jupyter Notebook, Spyder, Google Colab

Visualization Tools and Libraries

Basic understanding of Matplotlib and Seaborn

Areas of interest

Machine Learning, Deep Learning, Data Science and Computer Vision(CV)

Operating Systems

Windows and Android

ACHIEVEMENTS:

•Won man of the match award in VTU level competition in cricket.

•Champion in chess competition.

•Developed small games like Tic Tac Toe, Crab and Lobster, Flappy Bird using Corona sdk.

•Company achieved highest turnover in its history during my period and I was one of the core members.

CERTIFICATIONS:

•Jan 2020 – Advance Data Science course with Hands-on GPU from Netzwerk Data Science Academy an ISO certified institute.

•Nov 2019 – Complete Python Bootcamp: Go from zero to hero in Python3 by Udemy

•July 2019 – The Complete JavaScript Course 2019: Build Real Projects by Udemy

•July 2018 – Java and Manual Testing in ABC (Technology Training Institute)

PROFESSIONAL EXPERIENCE Aug 2018 – Jan 2020

Company

Time Plus Q Technologies Pvt. Lmt.

Project

Draw N Guess Multiplayer

Role

Game Developer

Technologies used

Javascript, Lua, Node.js, Pomelo Framework

Game Engine

Corona labs

Description

This game is all about drawing and guessing the word online with your friends and family. The objective of this game is, one player has to draw the word and the other players should guess the word and vice-versa.

Responsibilities

1) Worked on various game modes such as Realtime Mode, Turbo Mode, TurnBased Mode.

2) Worked on events updates like Halloween Event and Christmas Event.

3) Worked on Performance Enhancement of the Game.

4) Worked on Database and Query Optimization.

5) Worked on Google Cloud Platform(GCP) to handle the highly scalable servers and to fix the bugs using Error Reporting.

DATA SCIENCE PROJECTS:

Project 1: YOLO (You Only Look Once) Object Detection

Description

•Implemented YOLO object detection algorithm to detect the objects in a given image.

•Used Darknet Architechture with pretrained weights to build model.

•Object localization by drawing the best bounding box for all the objects in an image.

Tools and Technologies used

Python, Numpy, Matplotlib, Pytorch, CNN, OpenCV

Github link

https://github.com/Vinay-Kalmoodkar/YOLO-Object-Detection

Project 2: Face Mask Detection

Description

•This model is built using Convolution Neural Networks.

•Used Frontal Face Harcascade classifier to detect the faces by using the webcam. These face images are then passed to our model to detect whether or not a face contains the mask.

Tools and Technologies used

Python, Numpy, Matplotlib, OpenCV, CNN

Github link

https://github.com/Vinay-Kalmoodkar/Face-Mask-Detection

Project 3: Facial Landmark Detection

Description

•In this project a Convolutional Neural Network is trained to perform Facial Landmark detection which contains 68 distinct (X, Y) co-ordinate on the face.

•Used Computer Vision techniques to preprocess & transform image.

Tools and Technologies used

Python, Numpy, Pandas, Matplotlib, Pytorch, OpenCV, CNN

Github link

https://github.com/Vinay-Kalmoodkar/Facial-Landmark-Detection

Project 4: Wafer Fault Detection

Description

•Built an end-to-end classification methodology to predict the quality of wafer sensors based on the given training data.

•Built separate pipelines for data validation, insertion of data into database, model training and model prediction.

•During model training, data is first grouped using K-Means-Clustering algorithm and each groups are trained on separate models like RandomForestClassifier and XGBoost Classifier along with hyperparameter tuning in order to get the optimal model.

Tools and Technologies used

Python, Numpy, Pandas, Sql, Scikit Learn, Spyder

Github link

https://github.com/Vinay-Kalmoodkar/Wafer-Fault-Detection

Project 5: Air Quality Index Prediction

Description

•Extracted the AQI html data out from a website by applying Beautiful Soap and cleaned the data.

•Applied various regression techniques like Linear Regression, Lasso, Decision Tree Regression, Random Forest Regression and XGBoost Regressor and applied hyper parameter tuning to get the optimal model.

Tools and Technologies used

Python, Numpy, Pandas, Beautiful Soup, Jupyter, Spyder, Scikit Learn

Github link

https://github.com/Vinay-Kalmoodkar/Air-Quality-Index-Prediction

Project 6: Sentiment Analysis on movie reviews

Description

•Movie reviews were vectorized, tokenized and fed to the model to analyse the sentiment.

•LSTM-RNN model was built to fit and predict on validation/test data.

Tools and Technologies used

Python, Numpy, Pandas, TensorFlow, Keras, RNN

Personal Details:

DOB

24/08/1995

Address

#3-26, Saraswati godham, Gazipur, Gulbarga-585101

Languages Known

English, Hindi and Kannada

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