I'm a passionate Full Stack Developer, Machine Learning Enthusiast, and Software Engineer with a strong focus on delivering efficient and scalable solutions. I love solving complex problems, whether it's optimizing algorithms or building responsive web applications.

• 💼 Actively looking for a Full-time SDE or ML Engineer role & Currently working as a Software Developer Intern at OWP (California State University), where I developed the Storm Water Analytics platform using ReactJS and TypeScript.
• 🌐 I have 3+ years of experience as a Spring Boot developer, building microservices, REST APIs, and optimizing performance.
• 📚 Pursuing a Master's in Computer Science at California State University, Sacramento, with a GPA of 3.85, expected to graduate in December 2024.
• 🧠 Currently exploring Machine Learning and Generative AI with projects like Heart Disease Prediction using KNN and Email Generator using LangChain and ChromaDB.
• 🏆 Led a project on Parallel Branch-and-Bound Algorithm for the Sequential Ordering Problem to optimize performance & memory management.

Languages:
Java 8 | JavaScript (ES6) | TypeScript | Python | SQL | C++

Frameworks:
ReactJS | Redux | NextJS | Spring Boot | Jest | Flask | Node.js | JDBC | Selenium | JPA/Hibernate

Databases:
MongoDB | MySQL | SQLite | Neo4J | PostgreSQL

Tools & Technologies:
Docker | Jenkins | Git | Postman | JIRA | Confluence | SVN | Android Studio

AI/ML:
TensorFlow | PyTorch | Keras | Hugging Face | Scikit-learn | OpenAI API | LangChain | Llama

Here is the rewritten Projects section for your GitHub README based on the provided details:

• Email Generator using LangChain, Llama-3.1, and ChromaDB - (Aug 2024 - Sep 2024)
  Developed an intelligent email generator utilizing LangChain and Llama-3.1-70b, integrated with ChromaDB to analyze job descriptions. The system matches key skills and projects from my portfolio to generate personalized, professional job application emails.

• Parallel Branch-and-Bound Algorithm for the Sequential Ordering Problem - (Jan 2024 - Present)
  Implemented multithreading techniques such as work stealing, thread stopping, and dynamic load balancing in C++. This optimization significantly reduced processing times, enhancing performance for solving the Sequential Ordering Problem.

• Heart Disease Prediction using K-Nearest Neighbors (KNN) - (Oct 2023 - Nov 2023)
  Developed a machine learning model using K-Nearest Neighbors (KNN) to predict heart disease. The project incorporated feature scaling, Z-score normalization, and outlier removal, optimizing accuracy through thorough data preprocessing and evaluation with scikit-learn.

• Social Media Application on MERN - (Aug 2023 - Sep 2023)
  Built a full-stack social media platform, Thread, using the MERN stack. Designed and implemented both the front-end and back-end architecture for a seamless user experience.

• Linux Task Manager and Keyboard Tracing - (Aug 2022 - Dec 2022)
  Developed a GUI using tkinter for real-time and historical performance visualization with advanced filtering options. Built a custom keyboard interrupt handler in C++ for accurate real-time logging of keystrokes, achieving an accuracy rate of 99.5%.

• Focused on my Master's project, which involves optimizing memory management for the Traveling Salesman Problem (TSP), alongside enhancing computational efficiency with advanced algorithmic techniques.
• Actively exploring Machine Learning and AI through multiple hands-on projects, with a particular interest in Generative AI and advanced model optimization.

• 📧 Email: vikas.mishra0796@gmail.com
• 💼 LinkedIn: Vikas Mishra
• 🌐 Portfolio: My Portfolio
• 🖥️ GitHub: https://github.com/vikas-mshra

💡 "Stay curious, keep coding, and never stop learning!"