Software Developer | Data Engineering Enthusiast
I am Vandit Mehta, an ambitious and highly motivated individual with a passion for leveraging technology to solve complex problems. Currently pursuing my Master's in Applied Computer Science at Concordia University, I am also learning big data in an 8-month program by TrendyTech. I have honed my skills across various domains, achieving a CGPA of 3.7/4.3.
My proficiency spans diverse programming languages including Python, Java, C, C++, SQL, HTML, CSS, JavaScript, and PHP. I have a solid understanding of frameworks such as Git, Bash Scripting, Pandas, Flask, Django, Matplotlib, Pyspark, and Scikit-Learn. Additionally, I have experience with databases like MySQL, MongoDB, AWS DynamoDB, and PostgreSQL. My grasp of object-oriented concepts, data structures, and algorithms, coupled with a commitment to best programming practices, enables me to tackle complex challenges and maintain clean code.
In the ever-evolving data field, I have explored ETL processes, data integration, and using data to train algorithms for predictions or decision-making. If you're seeking a committed individual with a background in software development and a passion for data science and machine learning, let's connect to discuss how we can collaborate on cutting-edge solutions.
- Languages: Python, Java, C, C++, JavaScript, HTML, CSS, PHP, SQL
- Databases: PostgreSQL, MySQL, MongoDB, AWS DynamoDB, AWS RedShift
- Cloud Services: Amazon Web Services (AWS)
- Miscellaneous: Git, Jira, Docker, Jenkins, JetBrains tools, VS Code, Maven, Ansible, Kubernetes, Terraform
- Frameworks/Libraries: Flask, Django, PySpark, Boto3, CherryPy, Pandas, Numpy, Scikit-learn
Description: This project aims to detect and classify pneumonia using chest X-rays through Convolutional Neural Networks (CNNs). The goal is to improve pneumonia diagnosis, especially in resource-constrained healthcare settings, where accurate and timely diagnosis is crucial.
Tech Stack: Python, TensorFlow/Keras, OpenCV, Pandas, Numpy, PyTorch, torchvision, matplotlib, numpy
Architecting Scalable Distributed Systems: Leveraging AWS EKS, S3, Amazon ECR, Docker, and Kubernetes
Description: n this project, we dive into the principles and practices of distributed system design, utilizing a suite of advanced technologies to build and manage scalable, reliable, and efficient systems. Our approach leverages Amazon Web Services (AWS) tools, containerization with Docker, and Kubernetes orchestration to demonstrate key concepts in the field.
Tech Stack: Python, Pandas, Boto3, Pandas, AWS EKS, AWS S3, AWS ECR, Docker, Kubernetes
Description: This project implements a simulation of the Ford-Fulkerson algorithm for maximum flow in a network. The simulation includes the use of different augmenting path algorithms such as Shortest Augmenting Path (SAP), Depth-First Search (DFS), Maximum Capacity (MaxCap), and a Random augmenting path algorithm. The goal is to analyze the performance of these algorithms under varying graph conditions and provide insights into their efficiency and characteristics.
Tech Stack: Python, csv, random, heapq, time, collections, math
Description: Computation prediction of drug target interaction (DTI) and its solubility in water is vital for drug discovery. This project implements a research paper, "Estimating Aqueous Solubility Directly from Molecular Structure," by John S. Delaney.
Tech Stack: Python, AWS, Streamlit, Pycaret, RDkit, MySQL, Pandas, Numpy
Description: Engineered a user-friendly application that integrates with a facial recognition system, providing real-time attendance data and comprehensive reporting features, minimizing the spread of coronavirus during the pandemic.
Tech Stack: Python, OpenCV, Dlib, Tkinter, Face detection libraries
- LinkedIn: Vandit Mehta
- Email: contact.vanditmehta@gmail.com
- Pyspark Scenario Based Real Time Questions
- Distributed file storage and object-based file storage systems
- BigData - TrendyTech
You can check out my resume here.
I am always open to interesting projects and collaborations. Feel free to reach out!
Currently exploring:
- Big Data Technologies: Delving into various tools and frameworks for processing and analyzing large datasets.
- Advanced Data Engineering Techniques: Gaining insights into scalable data pipeline architectures and optimization strategies.
Thank you for visiting my GitHub profile!