deep learning
Projects with this topic
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Final project of course ML junior by Skillbox. Goal: Build model to predict client's loan default. Metrics: ROC-AUC
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Pipeline for deep learning network construction of host pathogen interaction (DLNet-HPI).
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Protocol for network and expression integration to identify potential defense gene in host-pathogen interactions
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Master thesis - Deep learning-based pairwise alignment of protein sequences using transformer architecture.
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Predicting pathogenic potentials of short DNA reads with reverse-complement deep neural networks.
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Prediction of age from X-Ray images of hand bones using deep learning models. We used 3 models: Shallow, ResNet50, and InceptionV4. The best result achieved was with a mean absolute error of 10 months using InceptionV4. The preprocessing of data included computer vision techniques like CLAHE filter and reducing channels, and also creativities such as using the Google MediaPipe library to detect hands and crop on them.
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Detector reconstruction of gamma-rays using deep learning.
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A Machine Learning approaches to identify genetic variants associated with disease
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This is the Python script which runs on Spud's Head Nano to detect faces. It communicates with other processors via ethernet.
This project was seeded by Mike Soniat's example. The first commit is Soniat's unmodified project.
See Soniat's files 'AI Face Following.pptx', 'AI Face Following.mov', and 'AI Face Following with Jetson Nano.mov' in the repository for more info.
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This is a project to train, use and analyze 2D and 3D neural networks for segmentation. It contains a UI and is implemented in pytorch and django as backend.
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Neural Network software for identifying atoms and atomic columns in High Resolution Transmission Electron Micrographs (HRTEM)
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這個專案展示在人工智慧相關技術方面的能力,包括數據預處理、視覺化、特徵選擇、模型訓練以及使用卷積神經網絡(CNNs)、循環神經網絡(RNNs)、長短期記憶網絡(LSTMs)和生成對抗網絡(GANs)等技術。
This project showcases our capabilities in AI-related technologies, including data preprocessing, visualization, feature selection, model training, and the use of advanced techniques such as CNNs, RNNs, LSTMs, and GANs.
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The Simple Pokémon Environment is an AI environment complient with gym that allows for training Reinforcement Learning agents in a simplified version of Pokémon Battles.
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Campus course: Deep Learning in the Social Sciences
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Implementation of Movement Aid for the Visually-Impaired by Using CNN based Learning Architecture
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This is the Python script which runs on Spud's Head Nano to detect and classify objects. It communicates with other processors via ethernet.
This project was seeded by Mike Soniat's example. The first commit is Soniat's unmodified project.
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This is the Python script which runs on Spud's Head Nano to recognize faces. It communicates with other processors via ethernet.
This project was seeded by Mike Soniat's example. The first commit is Soniat's unmodified project.
See Soniat's file 'AI Face Recognizer.pptx' in the repository for more info.
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