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We didn't read the submission instructions and I don't think our code works with the grading script. However we trained 3 models and they all have ROC AUC score of .95-.97
With the unprecedented accuracy of 66%, our model can evaluate the likely response of the user to AI-generated content by the Marky platform.
The advent of generative AI underscores the necessity of content creation for a successful business. We stepped up to help Marky revolutionize this process and save countless hours for clients.
In this project, we worked on a machine learning project where we trained a ml to recognise and predict a figure
the TD Hospital Exploration Prompt
A deep learning based predictor utilizing transfer learning methods using state of the art architectures.
A couple of juniors trying to understand how tensorflow works.
Uses feature selection and a neural network to predict whether a hospital patient will die given various health-related parameters.
We tackled the Pictionary Plunge challenge using pretrained CNNs that we finetuned on the provided sketch dataset.
Would clients like the AI generated content for their social media? This project allows us to predict if they would!
The model predicts patient survival using patient data and important health factors that may correlate to death.
Predicting whether a AI generated social media post would get approval from user.
Want to know if you're dead? Use our model.
developing an algorithm to predict what the user will accept or deny
Our project uses data to improve the security & comfort of our alumni. We hope to spread awareness of when students should be more cautious in certain campus areas by outputting a tailored report.
Model built to detect image matching using Quick, Draw
A Python machine learning model trained to predict the death status of a patient based on collected patient data from TDHospital.
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