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Bilal KaludiVerified

🗺️ Chicago, IL

About Me

Welcome! I am a current Data Science Master's student at San Diego State University and a Data Science Bootcamp graduate from Northwestern University. I also hold a Bachelor of Science degree from the University of Illinois at Chicago. Alongside my studies, I am employed as a Data Science Staff Assistant working on a DOE-funded project called CROCUS in collaboration with UIC and Argonne Lab. Additionally, I work remotely as a Data Analyst at Northshore Clinical Labs. I am also a Machine Learning Enthusiast. I love working with big data and have a passion for solving problems by thinking out of the box and being challenged.

As a recent Data Science and Analytics graduate from Northwestern University and a current Data Science Master's student at SDSU, I am skilled in Python, SQL, NoSQL, Big Data, Cloud Data, Tableau, HTML, CSS, Javascript, and have experience conducting data analytics and producing visualizations to inform research projects and initiatives. With over two years of experience as a Data Analyst at Northshore Clinical Labs, and over a year of experience as a Data Science Assistant at UIC, I have expertise in data integration, data cleaning, big data analytics, data visualization, business analytics, account management, and much more. Additionally, my bachelor's degree that I completed in the Summer of 2023 in Disability and Human Development with a focus on Disability Studies Research from the University of Illinois Chicago gives me a unique perspective on conducting data analytics on large datasets. As a big advocate for open source, I have created and published many different personal projects publicly and am proud to say that my open-sourced projects combined have achieved over 500,000 downloads. This reflects my commitment to contributing to the wider data science community and my dedication to the advancement of accessible, innovative technology.

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💡 My Skill Set

🧠 I’m currently learning Streamlit and how it can help to quickly make WebUI's, as well as how good it is with Machine Learning models.

❓ Ask me about anything related to Python, Streamlit, game development in Unreal Engine 5, working with Big Data or Machine Learning Models!

ℹ Fun fact: I trained my own Stable Diffusion Model that surpassed my expectations. You can find the model and view details here!

Kaludi's Frontend

👨‍💻 Frontend

Tools I Have Worked With

Streamlit Logo

gradio Logo

reactjs Logo

bootstrap Logo

html5 Logo

javascript Logo

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Kaludi's Backend

🔙 Backend

Tools I Have Worked With

dot_net_original_wordmark Logo

nodejs Logo

python Logo

pytorch Logo

linux Logo

gnu_bash Logo

mariadb Logo

salesforce Logo

wordpress Logo

flask Logo

Kaludi's Prog

‍💻 Programming Languages

Tools I Have Worked With

fcplusplus_original Logo

csharp_original Logo

java_original_wordmark Logo

HTML5 Logo2

python2 Logo

sql_server_icon Logo

javascript Logo2

CSS3_logo

Kaludi's Cloud

🛠️ Cloud Platforms & DevOps/Tools

Tools I Have Worked With

jenkins_icon logo

git_icon logo

gitlab logo

powershell logo

amazonwebservices logo

microsoft_azure_icon logo

Kaludi's Data Viz

📊 Data Visualization

Tools I Have Worked With

tableau logo

chartjs logo

d3 logo

highcharts logo

plotly logo

google_charts logo

fusioncharts logo

excel logo

Kaludi's Design

🎨 Design

Tools I Have Worked With

Adobe_Illustrator logo

Adobe_Photoshop logo

figma_icon logo

lightroom logo

aftereffects logo

blender logo

unreal_engine_logo logo

lucidcharts logo

💼 Portfolio

👋 Welcome to my portfolio!

With a passion for big data and a knack for creative problem-solving, I enjoy challenging myself to think outside the box.

Below are some of the projects I have worked on and created which include everything from training a text2image model, to a fully personalized recipe recommender.

You can learn more these projects by clicking on the links as well as viewing the written code.

Food Category Classification & Recipes Recommender

This app is a Food Category Image Classifier that recognizes 12 food categories and provides personalized recipe recommendations based on user preferences. Its user-friendly interface and recipe database integration make it an ideal tool for food enthusiasts seeking recipe suggestions.

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ChatGPT-Turbo SMS

ChatGPT-Turbo SMS is a Flask application that allows users to send SMS text messages to ChatGPT-Turbo using Twilio and receive instant responses. This application can be run locally or hosted on services like DigitalOcean to stay active 24/7 using tmux. The application uses Flask, Twilio, OpenAI, and ngrok python libraries.

VirtualBrainGPT: Digital Journal

VirtualBrainGPT is a digital journal streamlit application that leverages the power of OpenAI's Embeddings and Langchain to create a seamless and efficient journaling experience. With the capability to search and extract information from journal entries in seconds, VirtualBrainGPT becomes an indispensable tool for users who want to recall specific details from their past.

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Instagram Insights

Instagram Insights is a Python Streamlit application that allows you to analyze and visualize your Instagram data like users not following you back, users you aren't following back, and more.

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File Q&A AI Assistant

This app allows users to upload CSV or PDF files, or enter text and ask questions related to the content. The app uses OpenAI’s ChatGPT model to assist users in answering their questions about the uploaded content.

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AI Assistant: revChatGPT

This app allows you to chat with ChatGPT using a reverse-engineered API library called revChatGPT. Replies from the Chatbot are streamed back to the user in real-time, which gives the user an experience similar to how ChatGPT streams back its answers.

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US Census API Web Application

An Authentication protected web application created for Dr. Rooshey that allows users to query US Census data using the Census API. It fetches, displays, and analyzes the data based on the URL provided. Users can also download the fetched data and summary tables as CSV files. (Private repo due to request)

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US Refugee LIVE Data Visualization

A Python Streamlit application created for Dr. Rooshey that provides an interactive visualization of US refugee data for 2022. The data is retrieved live from a Google Sheet, allowing users to explore the most up-to-date information. Users can select different tabs from the sheet and refresh the data to load the latest information. The application will display a table and a line chart for the selected tab. (Private repo due to request)

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ARTificialJourney-v1.0-768

A Text2Image AI model trained on 768X768 images on top of Stable Diffusion 1.5 using the “artificial-journey style” keyword, which is designed to create high-quality close-up portrait pictures and landscape images in resolutions of 1024x768px, 768x1024px, and 768x768px. For best results, include detailed text with the prompt. Link 1 | Link 2

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ChatGPT-BingChat Prompt Generator

Generates ChatGPT/BingChat & GPT-3 prompts using this model trained by Kaludi. Enter a role and a prompt will be generated based on it.

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OpenAI Chatbot Web Interface

Interact with OpenAI's GPT-3 models in real-time using your OpenAI API. Choose from a selection of their best models, set the temperature and max tokens, and start a conversation. Delete the conversation at any time and start fresh.

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Quick Summarizer App

This is a Text Summarization Model that has been trained by Kaludi to transform long and complex texts into concise and meaningful summaries. Get a quick and accurate overview of any document in seconds, saving you time and effort.
Web Interface | Model | Dataset

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EurekaQA

EurekaQA is a Question & Answering Model that has been trained by Kaludi to analyze text data and automatically answer questions based on the information contained within. The model uses advanced machine learning algorithms to perform extractive question-answering, meaning it selects the relevant information from a given text document to present as the answer to the question.
Web Interface | Model | Dataset

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Reviews Sentiment Analysis App

A tool that has been trained by Kaludi to analyze the overall sentiment of customer reviews for a specific product or service, whether it’s positive or negative. This analysis is performed by using natural language processing algorithms and machine learning from the model ‘Reviews-Sentiment-Analysis’ trained by Kaludi, allowing businesses to gain valuable insights into customer satisfaction and improve their products and services accordingly.
Web Interface | Model | Dataset

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