Welcome to My Portfolio

Learn About My Projects

Building an AI Chatbot Based on Documents

Addressing company questions from clients or employees can be time-consuming, especially with extensive documentation. However, integrating AI and LLMs can accelerate this process, making it more efficient and enjoyable for everyone involved.

In this project, I developed a Q&A AI Chatbot (also known as RAG System) utilizing policy documentation. This program receives a question, searches for relevant context within its documents, passes the information to a local LLM, and generates an answer based on a prompt.

Building a Multi-Language RAG Pipeline

Building a local RAG System can protect a company’s privacy and data while reducing dependency on external APIs. However, dealing with documents in different languages it’s always a challenge: translating them to English requires resources such as time, money, and machine power.

In this project, I built a local RAG System that handles documents in various languages and formulates answers in the user’s native language. I used tools like Ollama to set up prompt rules and answers, along with HuggingFace for embedding.

Building a AI SQL Assistant

Many companies aspire to make data-driven decisions in their daily operations. However, tight timelines and a lack of technical knowledge can affect workflows, breaking deadlines and making data less accessible.

In this project, I have built an AI SQL assistant that takes a user’s question, connects to a database, writes SQL queries in the background, and returns readable raw results. This app also features a simple interface that makes the entire experience easy to navigate.

Building a Text-to-SQL AI App

During my journey in learning Data Science, I developed a particular affinity for SQL. However, the time spent on crafting these queries can distract you from the more critical tasks of analyzing data and connecting databases.

In this project, I developed an AI App that generates SQL queries based on simple English instructions. This application combines open-source LLMs and Python, and features an interactive user interface.

Building a Web UI for a Local AI Agent

Hello AI enthusiasts and Data Analysts. In this project, I have developed a user-friendly interface for Data Analysis utilizing an AI model with Streamlit, LangChain, Ollama, and Mistral. The project also incorporates libraries such as Pandas, Matplotlib, and Seaborn for data analysis and visualization.

Take The Shot!

Hello! In this case, I analyzed data from 1558 Call Of Duty players and found some interesting insights regarding their Level, Time Played and other skills. Click here to read more!

Building a Multi-Agent AI System

As AI technology continues to develop, I have been exploring how to combine the new tools emerging in today’s landscape. In my recent project, I built a Multi-Agent AI System that searches the web for data, saves its findings, passes the information to a writing agent and outputs a result based on a prompt. This project primarily utilizes Python, Ollama, and LangGraph. Click to read more!

Music Popularity Prediction with Python

Hello! I’ve been having some fun learning about Machine Learning and predictive algorithms. In this article, I use a data set with 227 music tracks to predict their popularity creating and training a model. Take a look for more!

Salary Prediction Using Machine Learning

I’ve been digging into the world of AI and Machine Learning, so I decided to work on a simple ML case using predictive modeling. Hope you like it!

Hired Or Fired?

For this case, I analyzed HR data using R to generate Linear Regressions, Box Plots and Welch-Two Sample tests. This helped me predict monthly income based on age, whether an employee would stay in the company or not, and other correlations. Click here to read more!

Let’s Get The Iron

For my next case, I go through iron mining data using Python. This approach and coding language was really useful to verify the success of the iron mining process. Click here to read more!

Dribble Pass & Shoot!

Hello! It’s me again! This time, I analyzed NBA data from Season 2021-2022 using Tableau. I found very interesting facts and insights and had a great time creating different visualizations. Click to read more!

Health is Wealth!

For this case, I use SQL to analyze data from 130 hospitals in the US and find very interesting and helpful insights for patients and medical professionals. Click to read more!

Where is The Money?

I had a lot of fun analyzing this data set from The International Development Association using SQL. It was really interesting to see how much money certain countries borrow and how much they pay back. Click to read more!

Welcome to Canada!

For this project, I explore government data to find insights and trends about international students that came to Canada between 2015 and 2023 using SQL.

Back To School!

In this case study from Data Analytics Accelerator, I was prompted to analyze the State of Massachusetts education data using Tableau. The main focuses were: What schools are struggling the most? How does class size affect college admission? What are the top math schools in the state?

Analyzing DoorDash Sales Throughout The Year

In this study, I analyze a real data set from DoorDash using Excel to find important insights about their customers and revenue. Click here to read more!