🚀 Advanced Data & AI Engineering Portfolio: Real-world projects and production-ready patterns to level up your AI skills—from building clean data pipelines to deploying RAG systems, AI agents, and intelligent dashboards.

Inspired by the recent movement of creating systems, not pages. This is a living library of deliverables that can be stylized to fit your next project. Each pattern is included within the pattern directory and can be optionally included into the final guide.

Python project for Market Basket Analysis. Generates synthetic retail transactions, mines frequent itemsets using Apriori & FP-Growth, derives association rules, and outputs CSVs + visualizations. Portfolio-ready example demonstrating data science methods for uncovering product co-purchase patterns.

WIP: [Portfolio] Please check this repository. This is Instagram clone app repository using MVVM pattern and modern technologies.

Curated list of the best designer portfolio websites for inspiration, UI patterns, UX case studies, and creative ideas.

A polished, accessible client-side password strength checker that estimates entropy, detects weak patterns, and provides actionable suggestions. Includes a built-in password generator, works fully offline with no network calls, and uses ARIA live updates for accessibility. Ideal for demos, portfolios, or frontend components.

[DEPRECATED] City of Philadelphia Pattern Portfolio

Stock Market predictions are one of the most difficult problems to solve, and during the looming days of recession it’s extremely difficult and next to impossible to do. This is because there are numerous patterns in the stock prices trend throughout the day and every variation from the normal trend could mean something new, since stocks is ever expanding and hence new problems and pattern in the trends are visible which needs to be studied but these new trends are usually generated each and every day possible of the trade and to keep up with the change is a very lofty task to do especially for an individual who has a large or even semi large portfolio to maintain over a period of time. Stocks and bonds are immensely important for a country’s economy to boom and it’s collapse means the collapse of country’s economy and since these markets are linked with every possible sector that contribute to the economy, mostly organised sectors, it’s collapse would be seen on every sector linked in those markets by what the economists call as “Ripple effect” and this goes other way around as well that if a particular sector’s firm performs poorly, then that would be reflected in the other firms of that sector.

Financial time series analysis and prediction have become an important area of re- search in today's world. Designing and pricing securities, construction of portfolios and other risk management strategies depends on the prediction of financial time se- ries. A financial time series often involve large dataset with complex interaction among themselves. A proper analysis of this data will give the investor better gains, but the existing methodologies focus on linear models (AR, MA, ARMA, ARIMA) and non- linear models (ARCH, GARCH, TAR). These models are not capable of identifying the complex interactions and latent dynamics existing within the data. Applying Deep learning methods to these types of data will give more accurate results than the existing methods. Deep learning architectures can identify the hidden patterns in the data and is also capable of exploiting the interactions existing within the data, which is, at least not possible by the existing financial models. The proposed work uses four different deep learning architectures (RNN, LSTM, CNN, and MLP) for predicting the minute wise stock price for NSE listed companies and compares the performance of the mod- els. The proposed method uses a sliding window based approach for predicting future values on a short-term basis. The performance of the models was quantified using error percentage.

[Communications Biology 2025 (under Nature Portfolio)] SpaCross is a comprehensive analytical framework designed for spatial transcriptomics data, aiming to enhance the accuracy of spatial pattern recognition and cross-slice consistency.

In tune with conventional big data and data science practitioners’ line of thought, currently causal analysis was the only approach considered for our demand forecasting effort which was applicable across the product portfolio. Experience dictates that not all data are same. Each group of data has different data patterns based on how they were sold and supported over the product life cycle. One-methodology-fits-all is very pleasing from an implementation of view. On a practical ground, one must consider solutions for varying needs of different product types in our product portfolio like new products both evolutionary and revolutionary, niche products, high growth products and more. With this backdrop, we have evolved a solution which segments the product portfolio into quadrants and then match a series of algorithms for each quadrant instead of one methodology for all. And technology stack would be simulated/mocked data(Hadoop Ecosystem) > AzureML with R/Python > Zeppelin.

Blog | Portfolio website builded with asp.net core,cqrs,hangfire,pure js, uow , repository pattern ...

An intelligent multi-agent AI assistant powered by Gemini LLM using the ReAct pattern to orchestrate five specialized agents (crypto, stocks, portfolio, RAG, web search) through MCP. Features a LangGraph supervisor with streaming Gradio UI.

A small Portfolio App with WPF in a Metro Design and MVVM Design Pattern.

A collection of multiple developer portfolio websites built with different technologies including React, Next.js, JavaScript, HTML, CSS, and Bootstrap. Each portfolio explores unique layouts, animations, and UI patterns for modern personal branding.

This Laravel-based Portfolio CMS provides an intuitive platform to manage and showcase personal or professional projects, making it easy to create and update dynamic portfolios. Implementing Clean Architecture, Repository Pattern, CQRS, Cache with Redis

Multi-page Spotify Dashboard built in Power BI with Home, Overview, Artists, and Songs pages. Shows insights on songs, artists, albums, popularity, trends, and listening patterns using interactive visuals, slicers, and Spotify-style dark UI. Focused on data storytelling, clean design, and portfolio-ready analytics.

This analysis aims to identify patterns which indicate if a client has difficulty paying their installments which may be used for taking actions such as denying the loan, reducing the amount of loan, lending (to risky applicants) at a higher interest rate, etc. This will ensure that the consumers capable of repaying the loan are not rejected. Identification of such applicants using EDA is the aim of this analysis. In other words, the company wants to understand the driving factors (or driver variables) behind loan default, i.e. the variables which are strong indicators of default. The company can utilise this knowledge for its portfolio and risk assessment.

Create React App with Next.js project #5. CRA with Next.js. React Eurobet MVC Pattern. TypeScript & React & Node.js & Firebase & Next.js & MVC Pattern. OnRender deploy. Portfolio Project #11

Create React App project #3. CRA. MVC. React & TypeScript & MVC. Technologies: MVC Pattern, Foundation, React, TypeScript. Portfolio Project #9

Created an Account Management System which manages a stock portfolio account and a bank account using C++ and STL *Created the capability to dynamically manage portfolios by allowing users to view price, buy shares, sell shares *Developed features to simulate bank account transactions like deposit/withdraw money and view history *Plotted variation in the value of portfolio over a period of time using MATLAB *Developed a Graphic User Interface using QT to make the whole system more User-friendly *Used Design Patterns like Bridge and Adapter to enhance the experience to ensure reusability of software

A personal portfolio homepage showcasing the skills and projects of a Full Stack Web Developer, built using the SASS 7-1 Pattern. Includes responsive design with navigation to different sections, like About Me, My Projects, and Contact.

A high-performance, aesthetically driven personal portfolio built with cutting-edge web technologies. This project showcases my engineering journey, selected works, and live contributions with a focus on premium user experience, modern design patterns, and smooth motion design.

A pattern portfolio for the City of Oakland based on GitHub's Primer

Visual Standards and Pattern Portfolio for CFA products

Pattern management system for Sublime Text 4 with portfolios, dynamic variables, and Find panel integration

- Portfolio risk management for long-term investors - Volatility pattern analysis for swing traders - Educational resource for AI/finance students - Prototyping base for algorithmic trading systems

Unsupervised Learning Projects – Research-oriented Python portfolio exploring clustering, customer segmentation, pattern discovery, and evaluation on real-world datasets using KMeans, DBSCAN, Agglomerative, and divisive methods.

USBlink is a modular Python-based USB security toolkit that detects and monitors suspicious USB activity in real time. It identifies BadUSB behavior, spoofed HID devices, anomalous patterns, and generates automated security reports. Designed for VAPT practice, cybersecurity labs, and technical portfolio demonstrations.

This case study aims to identify patterns which indicate if a client has difficulty paying their instalments which may be used for taking actions such as denying the loan, reducing the amount of loan, lending (to risky applicants) at a higher interest rate, etc. This will ensure that the consumers capable of repaying the loan are not rejected. Identification of such applicants using EDA is the aim of this case study. In other words, the company wants to understand the driving factors (or driver variables) behind loan default, i.e. the variables which are strong indicators of default. The company can utilise this knowledge for its portfolio and risk assessment.