Practical End to End Project Based Data Science Mentorship/Training program

Class planning

Education:
Bachelors (Information Technology): SASTRA Deemed to be University ( 2018-2022)

Udacity Deep learning NanoDegree

Mentoring Experience :

1. Junior Coach at Unschool :

• Managed and Mentored students by clearing doubts on the discussion forum.
• Conducted bi-weekly interactive, hands-on live sessions on Artificial Intelligence.
• Worked towards increasing the course completion rate by a minimum of 60% every month.
• Evaluated and Graded student's final projects.

2. Community Mentor :

• Conducted bi-monthly sessions on Machine Learning.
• Conducted hands-on Webinars with Machine Learning Experts in building mini-projects.

Work Experience :

1. Machine Learning Engineer (Omdena.com):

𝗣𝗿𝗼𝗷𝗲𝗰𝘁: Preventing Online Violence Against Children

𝗗𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻: In collaboration with Save the Children, working with technology for development and Child Protection teams to analyze data sources and build models to understand and prevent online violence against children.

𝗞𝗲𝘆 𝘁𝗮𝘀𝗸𝘀:

► One of the 60 people selected from 26 countries selected for this project.

► Led the team of 12 people responsible for data mining through newspaper articles, and other available data sources for analyzing the severity, causes, and actors of online violence against children from more than 20 countries.

► Coordinated with other teams to define and achieve the project's goals.

► Applied NLP techniques to analyze newspaper articles, and other available data sources to understand the severity, causes, and actors of online violence against children as well as predatory behavior in each country

𝗣𝗿𝗼𝗷𝗲𝗰𝘁: Understanding Sentiments, Thoughts, Aspirations of Youth

𝗗𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻: The project host, Foundation Botnar, is a Swiss-based foundation that champions the use of digital and AI to improve the health and wellbeing of children and young people globally.

𝗞𝗲𝘆 𝘁𝗮𝘀𝗸𝘀:

• Selected as one of the 50 collaborators across 21 countries for the project " Understanding youth sentiments across the world".
• Worked under two tasks -Twitter and Reddit data analysis with a team of 20 people.
• Collected 6 Lakh tweets and comments strategically for the past 5 years in English and cleaned them by removing unwanted information like URL, mentions, etc.
• Performed Data analysis of the cleaned text by using natural language processing and by using custom made code, extracted most used words in the text to understand the youth's thoughts.
• Extracted the sentiments of the youth before and after a certain event using Natural Language Processing and mapped the sentiments into various heat maps, plots that show the trend of a particular sentiment by clustering the data into country wise, event wise and periodically.

2. Deep Learning Intern (Mavoix Solutions) :

Worked with a Team of four building a personalized Recommendation System for Diabeat Application

Developed a Machine Learning Model to cluster patients of a similar type for efficient Recommendation to help in their day to day life