About me

Welcome, I'm Abhishek Tiwari, a post-graduate from the Central University of Haryana, Mahendragarh where my major was Data Science and Computer programming. I have a keen interest in Computer Programming from my graduation days and CUH has allowed me to pursue my interest in the Data Science & Machine Learning segment. I have researched a lot about Data Science with my sources via a few online materials and courses.
I have completed my six-month internship in Developing Machine Learning techniques in Cyber-Security related problems at CERT-IN ( Ministry of Electronics and Information technology ), New Delhi. I am seeking a full-time job opportunity and I'm willing to work anywhere in India.

Experience

CERT-IN 'Ministry of Electronics and Information Technology'

Project Intern, Jan 2019 – May 2019

Worked on developing intelligent models to overcome Cyber Security Problems on a huge database partitioned into many files. As a Project Intern, my core work was to obtain the dataset analyze it and create intelligent models and prove the effectiveness to the senior Scientist team.

Terra Economics and Analytics Lab (TEAL)

Data Science Intern, Dec 2019 – March 2020


1. Scrape the Websites (Creating Scrappers)
2. Data Engineering on Scrapped Data (PostgreSQL, Pandas)
3. Data Analysis (Tableau, Pandas)

Education

  • Central University of Haryana

    Master of Computer Application

    July 2016 - july 2019

  • University of Lucknow

    Bachelor of Computer Application

    July 2013 - jun 2016

  • Pt.D.D.U.Saraswati Vidya Mandir

    10+2 UP Board

    May 2013

Courses

Python for Data Science
NPTEL (IIT MADRAS)

Introduction to Machine Learning
NPTEL (IIT MADRAS)



Practical Machine Learning with tensor-flow
NPTEL (IIT MADRAS & Google)

Introduction to Probability and Statistics
Completed (View Marks IIT MADRAS)

Projects

Intelligent Phishing Web-page Detection System

This project can identify legitimate and Phishing web pages. In this project, the preprocessing of data is followed by the exploration of data. Applied various feature selection techniques on the whole dataset and trained our ML model on this low dimensional dataset to classify the Phishing web-pages.

Image Recognition Model

The model is capable of identifying the patterns on the dress. Dataset having a list of image URLs. Each URL has an image of a dress and a tag indicating the pattern on the fabric. The framework used for building this model is Keras & Tensor-flow and optimized by NADAM and ADAM. Approach, DataSet and results are available in the GitHub link.

Credit Card Consumption Prediction

Understanding the consumption pattern for credit cards at an individual consumer level is important for customer relationship management. This understanding allows banks to customize for consumers and make strategic marketing plans. Thus it is imperative to study the relationship between the characteristics of the consumers and their consumption patterns.

Spam E-mails filtration system

This project can identify Spam emails. The model was trained on the ENRON6 text dataset of the famous Spam email detection Competition hosted by Kaggle. This Project has two parts, the first part does preprocessing of data using NLP techniques followed by an exploration of data and the second part does various advanced classification techniques to Classify the Spam E-mails.

Skills

Python

Data Science

Machine Learning

Numpy

Pandas

OpenCV*

tensor-flow*

Keras*

Selenium

Seaborn

sckit-learn

SQL

Tableau

Data Analysis

EDA

Matplotlib