Saquib Hussain - Portfolio

Welcome, I'm Saquib Hussain

B.Tech. (Honors) CSE (Data Science) | Aspiring Data Scientist

Results-driven Data Science enthusiast with hands-on experience in machine learning, deep learning, and reinforcement learning, complemented by impactful internships, advanced projects, and strong coding skills.

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About Me

Hi 👋 there! My name is Saquib Hussain and I completed B. Tech. (Honors) CSE (Data Science) degree from UTD - Chhattisgarh Swami Vivekananda Technical University (CSVTU). I have a passion for coding and problem solving, and I'm particularly skilled in Machine Learning, Deep Learning , Python ,HTML , C/C++ , NumPy , Pandas , Seaborn , R programming and data base language MySQL. I completed my schooling at Jawahar Navodaya Vidyalaya, where I developed a strong foundation in problem solving and mathematics. In my free time, I love to read books (especially novels) and practice portrait sketch drawing. I believe that these hobbies help me stay creative and develop my analytical skills. I'm excited to connect with other professionals in the tech industry and learn from their experiences. If you're interested in discussing programming, data science, or anything else tech-related, feel free to reach out to me!

Education

Graduation - B.Tech. (Honors) CSE (Data Science): UTD-Chhattisgarh Swami Vivekanand Technical University (CSVTU), Bhilai, C.G., India

2021 - 2025 | CGPA: 8.58
Senior Secondary School/CBSE: Sun Valley Public School, Varanasi, U.P., India

2021 | 65.60%
Secondary School/CBSE: Jawahar Navodaya Vidyalaya (JNV) Bhadohi, U.P., India

2019 | 79.80%

Skills

Programming Languages

Python, SQL, R, C/C++, DSA(C++)

Libraries and Frameworks

NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, Keras, PyTorch, OpenCV, Streamlit

Data Science

Machine Learning Algorithms, Machine Learning Statistics, Reinforcement Learning, NLP, Deep Learning, Data Science pipeline (data cleansing, visualization, modeling, interpretation)

Other Skills

Hypothesis Testing, OOP, Excel, Git, GitHub, Google Colab, Jupyter, VS Code

Experience

Research Intern (Reinforcement Learning and Deep Learning) – IIT Jammu

Feb 2024 – Jul 2024

Researched and developed a Reinforcement Learning-Based Intrusion Response System (RL-IRS) by integrating the Bellman equation and hyperbolic tangent reward function into a custom RL model.
Implemented the VarDetect framework, generated attacker/non-attacker datasets (Fashion MNIST, CIFAR10), and calculated Maximum Mean Discrepancy (MMD) and Mahalanobis distances for threshold analysis.
Created adversarial samples using FGSM attack with ResNet50, extracted embeddings using VAE, and visualized datasets in 3D via PCA and evaluated the model’s performance with a confusion matrix (TP=974, FN=26, FP=387, TN=613).

Machine Learning Intern – iHUB at IIT Roorkee

Jul 2023 - Sep 2023

Implemented Python libraries (e.g., Matplotlib, NumPy, Pandas) and Machine Learning Algorithms (e.g., SVM, KNN, Naïve Bayes, Decision Tree, Random Forest, Linear and Logistic Regression and Apriori Algorithms).
Completed a project that “Explore different datasets with classifiers”
During the internship phase, I pushed all code to GitHub to secure my learning and project works in GitHub Repository.

Projects

MasterChef

MasterChef is a deep learning-powered (Transformer Architecture Based) application that transforms food images into personalized recipes using computer vision and natural language processing. Built with Streamlit for the frontend, it integrates advanced image processing and text generation techniques to deliver accurate dish identification and step-by-step cooking instructions.

View on GitHub

Object Detection and Tracking Algorithm

Object Detection and Tracking Algorithm Implementation for Real-Time Video Streams and Static Images.

View on Streamlit

Explore Different Datasets with Different Classifiers

This Streamlit app enables users to explore different classifiers applied to various datasets, offering real-time interactivity to select datasets, classifiers, and parameters, while visualizing data in a 2D space using PCA

View on Github

Facial Analysis App

The Streamlit Facial Analysis App is a simple web application that allows users to upload images and perform facial analysis on them. It utilizes popular libraries like OpenCV, DeepFace Numpy , Pillow , and Streamlit to create an easy-to-use interface for analyzing/predict the Age , Gender and Emotion of image.

View on GitHub