FIRE Capital One Machine Learning at the University of Maryland
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- College Park, Maryland
- https://go.umd.edu/ml
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2021-Malware-Detection-Classification
2021-Malware-Detection-Classification PublicMalware detection is an important process in modern computing to help protect various systems from getting infected. The goal for any project, program, or system that aims to detect malware is to p…
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2020-Object-Tracking
2020-Object-Tracking PublicObject tracking is a specific field within computer vision that aims to track objects as they move across a series of video frames. The goal of object tracking is to train a model and estimate the …
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2020-Image-Super-Resolution
2020-Image-Super-Resolution PublicSuper-resolution is the process of recovering a high resolution (HR) image or video from its low resolution (LR) counterpart. Our model uses a series of convolutional layers to extract, or learn, i…
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2020-Text-Generation
2020-Text-Generation PublicThe aim of this project is to create a Machine Learning Model that generates output sentences given an input sentence by training a Recurrent Neural Network (RNN) Model on hundreds of news articles…
Repositories
- 2022-t1-convolutional Public
We have created a song recommendation system based on user history. Our product takes in a user’s playlist(s) and recommends songs based on the playlist(s). The product uses the Spotify API to extract the features of a song (11 features in total), these range from danceability to tempo to instrumentalness. Using an aggregation function, the feature
umd-fire-coml/2022-t1-convolutional’s past year of commit activity - umd-fire-coml.github.io Public
FIRE Capital One Machine Learning at the University of Maryland - Official Stream Website
umd-fire-coml/umd-fire-coml.github.io’s past year of commit activity - 2022-t3-vector-quantization Public
User Uploads Soundtrack file. Uploaded track is run through Librosa functions to extract music features. Feature data is run through our Vector Quantization model to find the closest soundtrack in the dataset. Display Name of most "similar" soundtrack.
umd-fire-coml/2022-t3-vector-quantization’s past year of commit activity - example-scrum-project Public
umd-fire-coml/example-scrum-project’s past year of commit activity - 2022-t2-transformer Public
A variety of machine learning projects based the Transformer model, including: Song Recognition, MIDI Song Extender, Poem Generation, and Sentiment Analysis
umd-fire-coml/2022-t2-transformer’s past year of commit activity - 2022-t4-generative-adversarial Public
Audio generation when given a genre as natural language input. User inputs a genre tag into frontend. This tag is passed to the semantic similarity NLP model to determine the nearest tag within training the space, and implicitly coerces to (outputs) the found tag. This tag is passed to the audio generation model as input, which produces generated
umd-fire-coml/2022-t4-generative-adversarial’s past year of commit activity - 2022-t5-deep-q-learning Public
This project trains a DQN model to play a variety of Atari Games, including Q*bert. It includes a random agent, which generates gameplay based on the machine making random actions, as well as a trained model that attempts to make desired actions to win the game. Reinforcement learning is an area of machine learning that is focused on training agent
umd-fire-coml/2022-t5-deep-q-learning’s past year of commit activity - 2021-Image-Colorization Public
This image colorization model takes an input image, convert it to greyscale, then creates a realistic colorization of the image based off of the trained model. The model architecture utilizes the YCbCr colorspace in order to colorize the image, because Y is equivalent to grayscale, so the model has to predict only the Cb and Cr channels. The mod…
umd-fire-coml/2021-Image-Colorization’s past year of commit activity
