Darsh Parikh

AI/ML Enthusiast | Computer Science Engineer

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About Me

Passionate about AI/ML and skilled in Python, with a strong grasp of technical fundamentals and a collaborative mindset. Focused on utilizing technology to tackle intricate challenges and fostering positive working dynamics in collaborative settings.

Education

Skills

Programming Languages

Python, C, CSS, HTML, C#

Libraries / Frameworks

Pandas, NumPy, sklearn, Scikit-image, Headq, Folium, TKinter, Request, Matplotlib, Matlab, TensorFlow, Keras, PyTorch, OpenCV, GrovePI, Raspberry PI

Machine Learning

Time Series, Linear Regression, Logistic Regression, Decision trees, Random Forest, Predictive models, Deep Learning (CNN, RNN, ANN), Neural Networks, NLP, Confidence Intervals

Package Tools

GitHub, Git, Excel, Power BI, Tableau

Database

MySQL, SQL Server, Oracle, NoSQL, MongoDB

Soft Skills

Adaptability, Collaboration, Time management, Decision Making, Teamwork, Strategic Thinking, Self-Starting, Problem solving, Continuous Learning, Communication, Analytical Skills

Projects

AI-Powered Generative Chatbot Development

  • Developed an interactive chatbot system incorporating sophisticated language models, optimizing user interaction and enhancing user support processes using python.
  • Engineered a responsive chatbot solution, significantly reducing users query resolution time and improving user engagement through dynamic conversational interfaces.

Dialogue predictor Using NLP

  • Designed and implemented a predictive dialogue system harnessing natural language processing (NLP) techniques, leveraging external APIs to forecast conversational outcomes.
  • Developed a predictive dialogue model using advanced NLP methodologies and integrated external APIs, enhancing conversation flow prediction in interactive interfaces.

Generative image using stable diffusion

  • Implementation of a Stable Diffusion model for generative image synthesis.
  • Integration of the model into a Streamlit web application for interactive image generation in python.

Multi-Model Optimized route finding system

  • Utilization of Folium for interactive visualization of routes and geographical data, enhancing user understanding and engagement.
  • Incorporation of image processing techniques and OpenCV for pre-processing spatial data, enabling accurate feature extraction and analysis within the root-finding process. Additionally, implementation of the A* algorithm for optimal path-finding in graph-based representations of spatial data. Finally, deployment of the system using Streamlit for creating intuitive and interactive web-based interfaces, facilitating user interaction and feedback.

Internships

SAP code Unnati

AI-ML Internship

2024 - GTU

Infolebz IT Services Pvt. Ltd.

ML Internship

2024 - GTU

Events & Achievements

AI Conference 2023

September 15-17, 2023

Attended and presented a paper on 'Advanced NLP Techniques in Chatbot Development'

Hackathon: Code for Change

July 1-3, 2023

Led a team of 4 to develop an AI-powered solution for sustainable urban planning

Machine Learning Workshop

May 20, 2023

Conducted a hands-on workshop on 'Implementing Neural Networks with TensorFlow'

Tech Startup Pitch Competition

March 5, 2023

Finalist in the university-wide competition for an AI-driven healthcare solution