ITC’s Demo Night showcased outstanding projects from our talented Data Science Fellows.
What is Demo Night?
There were 13 teams in total, and every project blew our full-house crowd away with their creativity, skills and technology used in designing and creating impressive new applications.
The Project Demo Night is designed to give our participants a hands-on experience based on the subjects and state-of-the-art skills they have learned so far in the Data Science Fellows program. They had the opportunity to experience Data Science in an all inclusive, collaborative and high-level ideas and technology. These projects assist and give our participants material to present in their upcoming interviews. They have been working on these projects during the course of the program, constantly adding more of their learned skills and expertise.
Each topic was chosen by the team and have they have been given guidance and mentorship from Tech Mentors – Luis Voloch and Ido Kissos along with the assistance from the rest of the ITC staff. Resources and networking with experts in the field and tech companies was made available in order ensure projects of the highest quality.
If you weren’t there – here is a list of the project presentations that you missed.
Pardon my french
An accent detector, that given a recorded sentence can recognize the speaker’s accent (Neta, Mattan, Ziv, Shay W)
Mood detection through facial expressions
Mood detection through facial recognition – given a photo, detect weather the detected face is happy, sad, angry or surprised. (Arie, Remy, Elie S, Kevin)
Detecting skin cancer from metadata regarding patients, as well as a picture of a mole. (David, Aaron, Elisa, Dan)
Recognizing the sentiment of a sentence (good or bad) (Oren, Gilad, Anzor, Gabriel R)
Image Genre Analysis
Recognizing the genres of movies, based on their title and poster (Gabriel L, Elliot, Smadar, Guy, Matan)
Customer behavior in BM stores
Detect a customer entering a store, then analyzing his path before purchasing a product (by detecting the same customer that entered, at the cashier’s), in order to have conclusions about customer behavior (Juan, Diego, Felipe, Mariano)
Detection of biomechanics in sports
Detecting if a squat / push-up motion is done with the correct range of motion (Shalom, Roman, Roee, Tom)
Detect anomalies in skeletons (stick figures) produced as a part of a pose estimation algorithm. (Adi, Richard, Ari, Adam)
Create a presence sheet of a class, based on detecting and recognizing students. (Simon K, Jonas, Nathan, Jeremy B)
Answer questions given a relevant image and / or text. Can be useful to practive for exams, as well as for blind people who can ask “where are my keys” for example, take a photo of the room, and get an answer. (Elie C, Nicolas, Simon C, Noemie)
Detecting and classifying different heart conditions in X-Rays using image processing, including boundaries of the problematic area. The group also produced a project which is a motorcycle game, that learns to avoid obstacles (like GTA) (Michael, Jeremy E, Yair, Benjamin)
Record items in the store once put into the cart. The algorithm knows to detect the opposite motion and delete items that are pulled back from the cart and are unwanted, as well as notify the customer when the item he wishes to purchase is not found. This will allow the customer to skip the cashier and pay according to the cart he scanned along his journey in the store. (Shai A, Roey, Eitan, Nitzan)
Road Accident Prediction
Predict when a crime will occur on a certain district (based on data from Chicago), and predict what type of crime it will be. (Jennifer, Olivier, Garry)
Thank you to our Data Science students for all of their hard work these past months leading up to the completion of these projects!
Stay tuned for more updates and information as they begin their company projects.