Projects @ Data Science Retreat
All participants have the opportunity to engage in project work. Executing a substantial data science project shows your skills. See what data enthusiasts like you achieved at Data Science Retreat as a result of their training here, and imagination they brought with them. Get an impression of their experience by watching graduates talk through their projects - from the spark in inspiration to the finished product.
Dr. Juliana Du is a doctor in Human Genetics. She enrolled at DSR as part of Batch 13, and ended up building an app that uses computer vision to diagnose melanoma in humans.
A pertinent project for a Post-Truth Era, Diego Amicabile has worked across Europe in the IT industry for nearly two decades before coming to Data Science Retreat Batch 12 and starting work on a Fake News Detector (no, not "Generator"!) to expose fictitious news stories in the tech world.
Dr. Setareh Sadjadi was a chemical engineer in DSR Batch 13. She wanted to produce a project relating to climate change and the promotion renewable energy usage. She wrote a script to predict and forecast the photovoltaic power from a solar-panelled roof.
Dr. James Ryan was a theoretical physicist from Ireland when he joined Batch 13 of DSR in 2018. His time at the Retreat saw him produce a real-time road sign detector from scratch using a Raspberry Pi to be used in cars in a mere two weeks. How did he do...? Find out!
Petroleum enineer Antoine Montaut was - until his time at DSR - a petrophysicist in Austin, Texas. His project for DSR took a more theoretical approach, and combined ermergence and reinforcement learning, to produce visualisations on how reinforcement learning works, through the medium of the humble ant colony.
If you would rather see some code
Have a look at some projects' source and think how you could make them cooler. We want our participants to collaborate, and build a vibrant community.
Collaborative filtering (Alternating least squares (ALS) and the Universal Recommender (UR)) are evaluated to recommend interesting repositories for GitHub users according to their preferences: forks and stars.
CNN model to decide the direction while driving. Deconvolution mask for visulization to diagnose driving errors - what did the trained CNN model ‘see’ that caused ‘confusion’.
Control system for a parking lot based on reinforcement learning, where an AI can take control of the customer's car and dispach/retrieve it to/from a designated parking spot.
A repository of images of hand-written Cyrillic and Latin alphabet letters for machine learning applications. CoMNIST also makes available a web service that reads drawing and identifies the word/letter you have drawn.
It translates American Sign Language (ASL) to fingerspelled alphabet (26 letters) using transfer learning to extract features. This model is a real-time system with OpenCV - reading frames from a web camera and classifying them frame-by-frame.
With 130 songs in MIDI format of Ramones and the lyrics of all their 178 songs, a deep learning neural network was trained to write guitar and bass lines for Ramones-inspired music.