Welcome To
My Personal Portfolio

Welcome to my portfolio! I'm Sahil Lamba, a Masters of Science in Computer Science student at the University of Illinois at Chicago, showcasing my work in machine learning, AI, and web development.

Resume

Projects

Self Driving Car using Behavioral Cloning


An autonomous car model using a regression CNN to complete laps in a virtual simulator. Conducted data collection, augmentation, and pre-processing of frames and steering angle to maintain the car's position on the road, including sharp turns.


Stack
  • Python
  • Keras
  • Pandas
  • Numpy

Algorithm Visualization


The project is an interactive web tool designed to help users witness and understand the working of various search algorithms. It allows users to set a starting point, a goal, and obstacles along the path. By doing so, they can watch the algorithms navigate their way to the goal and compare their performance firsthand. The tool provides a hands-on learning experience that enables users to gain a deeper understanding of how search algorithms function in real-world scenarios.


Stack
  • React
  • JavaScript
  • HTML
  • CSS

Anime Face Generator


A GAN model on AWS cloud infrastructure to generate anime faces using a discriminator and generative model with 128-bit latent input. Used a Kaggle anime face dataset for the project.


Stack
  • PyTorch
  • GANs
  • AWS
  • Torch

Name Generator


The project serves as an example of how Natural Language Processing models can be used for generating new names or words that adhere to a specific naming convention. It involves using a Seq2Seq model architecture for Natural Language Processing (NLP) based on LSTM (RNN). The model is trained on a dataset of 2000 names using Python and Torch. A sampler was designed to generate 20 names, starting with any alphabet, using the trained model.


Stack
  • PyTorch
  • RNN
  • Seq2Seq
  • NLP

Shape Differentiating Model


This project involved building a multi-class classification model using Convolutional Neural Network (CNN) written in Torch and Python. The model was trained on a dataset of 90,000 images, each with dimensions of 200x200 pixels, and containing 9 classes of different shapes. The model achieved an impressive accuracy rate of over 98%


Stack
  • PyTorch
  • CNN
  • Matplotlib
  • Numpy

Handwriting Recognition Web - App


This project aimed to build a Machine Learning (ML) model that could recognize handwritten digits from 0-9 using Convolutional Neural Networks (CNN) in Keras and Python. The model achieved an impressive accuracy rate of over 99.9% on the well-known MNIST digit dataset. To make the model more accessible, a user-friendly web application was developed using Flask container.


Stack
  • TensorFlow
  • CNN
  • Flask
  • JavaScript

Technologies

I've Worked with a range of technologies in ML, AI and web development world.

  • Machine Learning

    Proficient in Regression,
    Classification, Ensemble
    methods, and Deep Learning
    with a focus on Computer
    Vision, including CNN,
    RNN, and GANs.

  • Artificial Intelligence

    Experience with
    Markov Decision models
    and Reinforcement Learning
    models.

  • ML/AI Tools

    Experience with
    PyTorch, Keras, Numpy,
    Scikit-Learn, OpenCV,
    Python, MatLab.

  • Data Science and Big Data

    Experience with Data
    Science tools such
    as Beautiful Soup,
    Selenium, Spark.

  • Front-End

    Experience with
    React.js

  • Back-End

    Experience with
    SpringBoot, Node
    and Databases.

Timeline

Personal Accompalishments

20+

Open Source Projects

6

Academic Paper Publications

3.85

Current cumulative GPA

Member of UIC Badminton Team

Transforming data into insights, one model at a time.