Experienced Machine Learning Engineer with a demonstrated history of working in the sports industry. Skilled in Data Science, Neural Networks, OpenCV, Computer Vision, and Scikit-Learn. Strong engineering professional with a Master of Technology (M.Tech.) focused in Computer Science from International Institute of Information Technology, Bhubaneswar.

1. POONAM AGRAWAL
email: poonam.agrawal12@gmail.com
Phone: +91-8319239886
Profile
Data Scientist at FANLYTIKS, Master of Technology in Computer Science from IIIT-Bhubaneswar.
Experience Details
• Believe in writing Maintainable code,constantly follow PEP8,pylinters,git.
• Hands on experience in developing production ready models, used TF-SERVING,flask.
• Hands on experience in different framework’s like Keras,Tensorflow.
• Hands on experience in handling diverse data with strong ML concepts and libraries.
• Strong knowledge of computer science fundamentals, data structures, algorithms.
• Strong passion of data driven research and working in fast-paced environment.
Technical Skills
Languages : C, C++
Script : Python
Framework : Flask
Libraries : Opencv,Scikit-Learn,Keras,Tensorflow
Technical Exposure : Machine Learning, Neural Networks,
Computer Vision, Web Scraping , NLP, Google Cloud
Database : Elasticsearch
IDE : Spyder, Pycharm, Postman
Project Details
1. Image Captioning : In this project, a generative model based on a deep recurrent
architecture that combines recent advances in computer vision and machine trans-
lation and that can be used to generate a reasonable description in plain English is
implemented. It is based on a convolution neural network that encodes an image into
a compact representation, followed by a recurrent neural network that generates a
corresponding sentence.
2. Profit prediction for fantasy game: We needed to determine/understand what will be
the profit if there,in a fantasy cricket game. I had done univariate,bivariate,multivariate
analysis for analytics and used Regression techniques for finding profit.The degree of
error in Regression was 0.16.
3. Visual Similarity : This Project takes a folder of various images as the input query and
clusters images based on image content. This approach clusters semantically-relevant
images from the input folder database.
• Used K-means on the top of extracted features from Inception Net for finding
cluster of images.
• Kneed is used to find optimal number of clusters for K-Means.
4. Brand Exposure : Verified brand exposure for certain clients.

2. • Trained many object detection models (YOLO v2 , SSD 512,Faster - RCNN).
• Used CTPN for scenic text detection.
• Made an API for the same.
5. Face Recognition: First, a face detector is used to localize faces in images. Second, with
the facial landmark detector, the faces are aligned to normalized canonical coordinates.
Third, the Face Matching module is implemented with these aligned face images.
6. Image based Document Classifier:In production environments, it is crucial to perform
accurate and time-efficient training.The approach was to train a fine tuned model on
top of Inception Net.
• Trained Vanilla CNN, got an accuracy of 68%.
• Trained Transfer Learning on the top of Resnet50 , got an accuracy above 98% .
• Added ensemble model on top of transfer learning for improving accuracy.
Education
June 2017 Master of Technology in Computer Science
International Institute of Information Technology, Bhubaneswar
Thesis: “Classification Of Tweets” | Advisor: Prof. Ajit Kumar Das
CGPA: 6.97
June 2013 Bachelors of Engineering in Information Technology
Shri Shankaracharya Engineering College, Bhilai
CGPA: 7.76
Personal Data
Name: Poonam Agrawal
Date of Birth: 26 July 1991
Father’s Name: Sri Kuleshwar Agrawal
Language Known: English,Hindi
Address: Bangalore,India
Poonam Agrawal