About Me
Introduction
Hello!
My name is Suvaditya Mukherjee. I am a student of the Bachelors in Artificial Intelligence Programme at NMIMS MPSTME, Mumbai.
I have played around and dabbled in many different disciplines of Computer Science in a quest to find out what excites me the most, and I have realized that Deep Learning and its applications in solving Real-world problems is the best way I see myself utilizing my skills for bettering the community.
I am a former Lead of the Google Developer Student Club at NMIMS MPSTME Mumbai and the former Co-Head of the Technical Software department at the International Society of Automation, NMIMS MPSTME Mumbai.
I have formerly interned for 2 months at Mosaic Wellness Pvt. Ltd. as a Software Engineer Intern
Technology Experience
- Deep Learning : Tensorflow/Keras, PyTorch, Weights&Biases, Optuna
- Machine Learning : Scikit-Learn, Pandas, Matplotlib, NumPy, CuPy, Seaborn, OpenCV
- Cloud Technologies : Amazon Web Services, Google Cloud, Heroku (Salesforce)
- Mobile App Development : Java, Flutter(Dart)
- Web Development : React, Node.js, Bootstrap, HTML/CSS
- Languages : Python, C++, Java, Dart, JavaScript, Rust (Beginner)
- Specialized Software : SOLIDWORKS (Beginner), Wireshark (Beginner)
- Containerization : Docker, Kubernetes
Certifications and Awards
- Google Inc. : GDSC Lead Tenure Completion
- IET MPSTME Hack & Code : Runner-up (2nd Prize) with Aaryadev Chandra, Dev Chandan and Shireen Chand
- Udacity : AWS Machine Learning Foundations
- LinkedIn : Advanced Linux - The Linux Kernel
- LinkedIn : PyTorch Essential Training - Deep Learning
- LinkedIn : Tensorflow - Neural Networks and Working with Tables
- LinkedIn : Unix Essential Training
- Coursera : Building Modern Python Applications on AWS
- Kaggle : Intermediate Machine Learning
- Kaggle : Intro to Machine Learning
- Kaggle : Intro to AI Ethics
- Kaggle : Pandas
- Kaggle : Python
- Stepik : Data Structures
- Coursera : Programming for Everybody(Getting Started with Python)
- Goldman Sachs : Engineering Virtual Program