Working as an independent programmer who specializes in application development and technologies, with experience working on industry projects, my aim is to create a platform that distributes applications under one common name in order to support various industries in better understanding and utilizing computer application technologies.
Check out some of my work below! 😀
Easily create thousands of amazing NFT artworks in just minutes with the Gensky NFT Generator.
Customize your battery charging screen with battery charging animation and give an attractive look to your charging screen.
Paper Trading: Stock Simulator uses real data of markets to help enthusiasts with real-world practice to gain experience without having to invest real money.
Random enemies will appear and you have to shoot and kill them with your bow before they can kill you.
Run, jump, shoot, and climb on the walls just by simply tapping. Collect coins, keys and run to complete the pocket levels at your pace.
A small turn/tile-based rouged-like style game. You are trying to survive the day and your only two enemies are zombies and food rations.
This game was made in 3 days for a game development class time crunch stress project and shown at a local convention called the Pomona TechJam.
Made with a team of 6, this was a team effort and contribution for a game development course project.
A modern version of the classic now has better graphics, nice sounds and better spaceship navigation.
Welcome to the wonderful and colorful, soft and served, world of Scoop Foodies NFTs. Here you'll find 1000 1-of-1 Kawaii Scoop Foodies NFTs on the Polygon Blockchain.
Computer-generated imagery using artificial intelligence applications of computer graphics. Such applications are used to contribute and create beautiful artwork.
55 Creature Verse NFTs on the Polygon Network. Join the herd!
In this project, I use deep/machine learning techniques in order to predict house prices in the Boston suburbs. A heavy use of linear regression was implemented in order to find the intercept and coefficients which resulted in an error of ℓ(𝑤) =12𝑁∑ [𝑡(𝑖) − 𝑦(𝑥(𝑖))]𝑁2 𝑖=1 on training data and test data, respectively.
In this project, I developed a Deep Learning model in Python using Keras in order to predict the age of an individual only given a portrait photograph. This is a regression/classification problem, and the evaluation is based on the Mean Squared Error function for ranking.
The goal of this project was to develop autoencoders for image segmentation that could segmentate hair from a face given only a standard portrait image.
The goal is to analyze data in order to enter swing trades. Simple Jupyter notebook showing data acquired/created and the logic used to base such decisions.
Using Machine Learning Techniques to Estimate Stock Growth
Predicting how the stock market will perform is one of the most difficult things to do. There are so many factors involved in the prediction – physical factors vs. physiological, rational and irrational behavior, etc. All these aspects combine to make share prices volatile and very difficult to predict with a high degree of accuracy. In this project, I worked with historical data about the stock prices of a publicly listed company. I implemented a mix of machine learning algorithms to attempt and predict the future stock price of the given company, first starting with a simple algorithm like averaging and then moving on to advanced techniques like Auto-Regressive Integrated Moving Average (ARIMA) and Long short-term Memory (LSTM).