About

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I'm a passionate AI Engineer with expertise in Machine Learning, Deep Learning, Computer Vision, NLP and Agentic AI. I’ve acquired hands-on experience building ML models, working with imbalanced datasets, and applying state-of-the-art techniques like data augmentation and model fine-tuning. Additionally, I’ve worked with GANs, diffusion models, computer vision tasks, and natural language processing solutions.
My recent work includes developing a Retrieval-Augmented Generation (RAG) chatbot integrated into this portfolio, designed to answer questions about my projects, skills, qualifications and much more.

My qualifications:

Bachelor in Engineering from Jamia Millia Islamia
IBM AI Engineering Professional Certificate

If you're interested in learning more about my work or want to discuss potential collaborations, feel free to reach out!

Skills

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Machine Learning

I have hands-on experience with a variety of supervised and unsupervised machine learning techniques. My expertise includes a deep understanding of algorithms such as K-Nearest Neighbors (KNN), Decision Trees, and various regression and classification models.

Deep Learning

I have extensive experience training deep neural networks and possess strong theoretical and practical knowledge of deep learning algorithms, including CNNs, LSTMs, Transformers GRUs, GANs, Autoencoders, and Diffusion models.

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Computer Vision

I have solid experience in computer vision, with expertise in building and deploying models for tasks such as image classification, object detection, and image generation. I am well-versed in deep learning techniques, including CNNs, GANs, and Autoencoders, and have worked with frameworks like OpenCV, TensorFlow, and PyTorch to solve various computer vision challenges.

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NLP

I have strong expertise in Natural Language Processing (NLP), with experience in building models for tasks such as text classification, sentiment analysis, and language generation. I am proficient in working with algorithms like LSTMs, GRUs, Transformers, and pre-trained models such as BERT and GPT. Additionally, I have used libraries like NLTK, spaCy, and Hugging Face to implement and fine-tune NLP solutions.

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Generative AI

I have hands-on experience with Generative AI, including building models for tasks such as text generation, image synthesis, and speech-to-text conversion. I am proficient in working with GANs, VAEs, Diffusion Models, and Transformers, as well as fine-tuning large language models like GPT. Additionally, I have utilized tools and frameworks such as Hugging Face, LangChain, and PyTorch to develop innovative generative solutions.

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HTML, CSS

I have practical experience with front-end web development, having built my portfolio website using HTML, CSS, and JavaScript. I am proficient in creating responsive designs, styling web pages, and implementing interactive elements to enhance user experience. This experience has given me a solid foundation in web technologies and the ability to present my projects effectively online.

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Agentic AI

I have hands-on experience with agentic AI, having built a Retrieval-Augmented Generation (RAG) chatbot using LangChain, FAISS, and PythonAnywhere. This project involved integrating retrieval mechanisms with generative models to deliver accurate and context-aware responses. Through this work, I gained practical knowledge of combining search-based methods with AI, deploying applications on cloud platforms, and optimizing chatbot performance for real-time interaction.

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Python

I have strong proficiency in Python, using it extensively for developing machine learning models, deep learning solutions, and AI applications. I am well-versed in popular Python libraries such as NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Additionally, I have applied Python in diverse areas, including data analysis, web development, and automation, showcasing my ability to leverage the language effectively for both research and production-level projects.

Projects

RAG CHATBOT

A chatbot that responds to user queries about my portfolio in real-time. Click the button below to start chatting!

INTERPRETING SIGN LANGUAGE

A computer vision model capable of interpreting sign language from images.

SENTIMENT ANALYSIS

This model analyzes input text to determine sentiment, categorizing it as either 'Positive' or 'Negative.'

HEART DISEASE PREDICTION

This model predicts the likelihood of heart disease in a patient by analyzing symptoms such as blood pressure, cholesterol levels, and chest pain.

Ink2Pixel

Ink2Pixel seamlessly converts handwritten text from an image into a digital format.

RULE BASED TEXT ANALYSYS

This program is designed to provide comprehensive insights into any given text by performing detailed analysis across several key metrics.

EMOTION BASED YOGA SESSION RECOMMENDER

This app extracts emotions from audio inputs and recommend tailored yoga sessions.

DECISION TREE CODE FROM SCRATCH

This repository contains the python code for Decsion tree for Binary Classification.