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Mathang Peddi

Welcome to my GitHub! I'm Mathang Peddi, an Aspiring Software Engineer blending the worlds of Software Engineering and Machine Learning, and I'm thrilled to invite you to explore my journey in the enchanting world of technology right here on GitHub!

This is my personal portfolio website mathangpeddi.netlify.app built with Gatsby and hosted with Netlify

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πŸŽ“ From Foundations to Frontiers: My Engineering Chapter

At PES University, my journey through the Bachelor of Technology in Computer Science Engineering program, spanning August 2018 to May 2022, was a blend of rigorous academics and explorative projects. With a notable GPA of 8.5, the curriculum ventured beyond traditional engineering disciplines, embracing areas like Data Structures and Algorithms, Full Stack Development, and Machine Learning. Little did I know, this was just the beginning of my tech adventure!

🏫 Scholarly Expedition: The Georgia State Chronicles

Fast forward to today, where I'm on an exhilarating quest for knowledge at Georgia State University, pursuing a Master's in Computer Science. With a stellar GPA of 4.0/4.0, I'm navigating through the realms of Data Science, Big Data Programming, NLP, and more. As a Research Assistant at the Evidence-Based Cybersecurity Lab [EBCS], I'm not just studying; I'm actively contributing to the magic!

πŸ’» Technological Arsenal: Skills and Frameworks Galore

Armed with spells like Python, R-Programming, C++, and React, I've woven data magic with Pandas, NumPy, and Scikit-learn. I've danced in the clouds with MySQL, MongoDB, and even summoned the mighty AWS Services. But wait, there's more! I've wielded Tableau, Django, and a bunch of other tools like a tech wizard.

πŸ› οΈ Professional Odyssey: Navigating the Tech Terrain

My professional narrative weaves through dynamic roles and projects, each enhancing my acumen in technology and innovation:

Evidence Based Cyber Security Research Group | Research Analyst/Data Scientist | Jan 2024 - Present

Performed data analysis and created visualizations from multi-modal unstructured data scraped from Telegram channels, utilizing EDA techniques to flag fraudulent admin postings, thereby reducing data breaches. Operated data cleaning and data management techniques to ensure the quality and accuracy of data for analysis.

Citrix Systems | Software Engineer | Jan 2022 - Dec 2023

With a strong foundation in both software engineering and data science, I have consistently delivered impactful solutions by blending advanced technical skills and analytical prowess. My experience spans developing core features such as Activity Manager of Citrix Workspace UI (WSUI) for large-scale applications, optimizing performance, and leveraging machine learning to drive user engagement and business insights.

πŸš€ Chapter 5: Epilogue: The Future Awaits

As I continue my journey, I'm on the lookout for exciting roles as a Software Developer/Data Scientist/Data Analyst. If you're on a quest to build powerful data-driven spells, collaborate on enchanting projects, or just share your own tech tales, I'm all ears! Reach out, and let's make the magic happen. Happy coding, and may your code be ever bug-free! ✨

SKILL SETS:

Programming Languages: Python (Pandas, NumPy, Scikit-learn), R-Programming, JavaScript, C++

Databases and Cloud: MySQL, MongoDB, PostgreSQL, AWS Services

Tools and Frameworks: Agile, Bash, Git, Excel, Microsoft Office, Tableau, Django

Web Dev: HTML, CSS, TypeScript, SQL, Node JS, React, Bootstrap, Flask

Data Science and Machine learning: Matplotlib, Seaborn, NLTK, TensorFlow, Keras, Deep Learning (Neural Networks, Transformers, LLMs), NLP

For Future Opportunities/ Collaborations, Contact me @

E-mail: [email protected]

LinkedIn: Connect with me

Contact: +1 (404)-452-7630

Mathang Peddi's Projects

algorithms-visualizer icon algorithms-visualizer

This is a website designed to simulate the step-by-step working of common algorithms, including Searching, Sorting, and Machine Learning techniques such as K-Nearest Neighbors, Clustering, Merge Sort, Quick Sort algorithms etc.

c-plus-plus icon c-plus-plus

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

cotton-disease-prediction icon cotton-disease-prediction

Created a web app that determines a leaf/plant as diseased/normal. I had used the traditional CNN method and achieved an accuracy of 82% With the help of Transfer Learning and the ResNet152V2 model, was able to get an accuracy of 98% for the dataset

crime-analysis-los-angeles icon crime-analysis-los-angeles

This project focused on analyzing and visualizing crime data in Los Angeles. The project includes exploration to identify crime patterns and trends. It employs various statistical and machine learning techniques to provide actionable insights for public safety and urban planning.

glassdoor-job-salaries icon glassdoor-job-salaries

Glassdoor Job Salaries is a comprehensive data science project that predicts job salaries using data from Glassdoor. It aims to help job seekers and employers gain valuable insights into salary trends and make informed decisions.

hacktoberfest icon hacktoberfest

Make your first PR! ~ A beginner-friendly repository made specifically for open source beginners. Add your profile, a blog, or any program under any language or update the existing one. Just make sure to add the file under the correct directory. Happy hacking!

hacktoberfest-2020 icon hacktoberfest-2020

Let's tackle the Climate-Change together with Open-Source 🌍 + πŸ‘©β€πŸ’»

laptop-prices-predictor icon laptop-prices-predictor

Laptop Prices Predictor is an end-to-end data science project that accurately predicts laptop prices using machine learning algorithms. The project involves data collection through web scraping, feature engineering, model training, and deployment of the predictive model. It offers a comprehensive solution for estimating laptop prices.

neighbourhood-segmentation-using-foursquare icon neighbourhood-segmentation-using-foursquare

This is a project that segments neighborhoods based on venue data. It involves data collection through Foursquare’s API, feature extraction, and clustering to identify distinct neighborhood segments. The project provides valuable insights into neighborhood characteristics.

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