Welcome

Hello, my name is Juan Cruz. I am an AI Engineering student at Neumont College of Computer Science, where I am developing deep expertise in machine learning, intelligent systems, full-stack web development, and modern software engineering practices.

On the web development side, I design and deploy full-stack applications using Node.js and Express with MongoDB for data persistence, one of which is currently live on Render. I am comfortable working across the entire stack, from designing RESTful APIs and database schemas to crafting responsive front-end interfaces. I also containerize my development environments using Docker, keeping deployments consistent and reproducible.

In the machine learning space, I have worked with regression, classification, and clustering algorithms using scikit-learn, pandas, and NumPy, applying these models to real-world public datasets from Kaggle and sklearn. I am passionate about the intersection of data, intelligent systems, and practical software, and I am actively seeking opportunities to grow in this space.

My Projects

Full-Stack Web Applications

Gig Tracker 🌎 Live on Render

A full-stack gig tracking web application built with Node.js and Express, backed by a MongoDB database. Features full CRUD operations on gigs, and a clean responsive front-end. Deployed to Render with environment-based configuration.

Inventory Tracker+ 🌎 Live on Render ⚙ In Progress

A full-stack inventory management application currently in active development. Built with Node.js and Express, using EJS templates for server-side rendering. The application follows a monolithic architecture where a single root file coordinates both frontend and backend routes independently, establishing a clean separation between the API layer and the Data Access Layer (DAL), this is a pattern shared with the Gig Tracker. Data is persisted in MongoDB and the app is deployed on Render.

Machine Learning & AI

Predictive Modeling with Regression & Classification

Applied supervised learning techniques to public datasets, sourced from Kaggle for a class assignment. Implemented and compared multiple models including logistic regression, random forests, Decision Trees, K-Nearest Neighbors, and MLP classifiers evaluating performance with metrics such as accuracy, precision, recall, and F1-score. Preprocessing pipelines were built using pandas and NumPy to handle missing data, feature scaling, and encoding.

Foundational Projects

Scrambler — Encryption Engine

A cryptography-focused Java application implementing classical encryption algorithms, including Caesar cipher and substitution-based methods, to encrypt and decrypt arbitrary text. Built during my first programming course, this project established my foundation in string manipulation, modular code design, and algorithmic thinking.

Image Manipulation Tool

A Python command-line utility for pixel-level image processing, supporting grayscale conversion, brightness adjustment, color channel filtering, and edge detection. Originally a course assignment, this tool has grown into a personal utility I continue to refine. It reflects my interest in applied algorithms and software that solves tangible problems.

My Skills

Machine Learning & AI

Hands-on experience with supervised and unsupervised learning using scikit-learn. Have trained, tuned, and evaluated regression, classification, and clustering models on real-world datasets from Kaggle and sklearn. Proficient in the full ML workflow including data exploration, preprocessing, feature engineering, model selection, and evaluation using metrics like accuracy, F1-score, and RMSE.

scikit-learn pandas NumPy Matplotlib Regression Classification Clustering

Full-Stack Web Development

Experienced in building and deploying complete web applications using Node.js and Express on the back end, with MongoDB for data persistence. Comfortable designing RESTful APIs, managing authentication flows, and connecting front-end interfaces to back-end services. Have deployed multiple projects to production on Render.

Node.js Express REST APIs HTML CSS JavaScript Render

MongoDB & NoSQL Databases

Practical experience designing and querying NoSQL databases using MongoDB. Skilled in schema design with Mongoose, building aggregation pipelines, managing document relationships, and optimizing queries for full-stack applications. I understand when a document-based model is the right fit and how to structure data effectively within that paradigm.

MongoDB Mongoose NoSQL Aggregation Schema Design

Docker & Containerization

Use Docker to containerize applications, ensuring consistent environments across development and production. Familiar with writing Dockerfiles, managing multi-service setups, and integrating containerization into full-stack deployment workflows.

Docker Dockerfile Containerization DevOps

Python

Python is my primary language for data work and automation. I have applied it extensively in machine learning pipelines, data analysis, and scripting. Proficient with the scientific Python ecosystem and comfortable building both quick utilities and structured, multi-module projects.

Python OOP Scripting Automation Jupyter

Languages

Fluent in both English and Spanish, with professional written and verbal communication skills in both. Currently relearning French. Multilingual communication is an asset I bring to collaborative and international environments.

English Spanish French (learning)

Get In Touch

● Available for Opportunities

Whether you have an internship opportunity, a project idea, or just want to connect — my inbox is always open. I look forward to hearing from you.

✉

Email tonocruz9000@gmail.com

GitHub github.com/CruzJua

👥

LinkedIn linkedin.com/in/juan-cruz