machine learning
Projects with this topic
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Collection of completed data-mining (university course) on python
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Workshop held in the Summer School on Optimization and Machine Learning at ZIB in Berlin, 2023.
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Nous avons entrepris un projet d'apprentissage automatique pour prédire des maladies en analysant les données symptomatiques et médicales. Notre modèle sophistiqué, basé sur des techniques d'apprentissage automatique avancées, évalue les symptômes pour fournir des prédictions précises. Avec une interface API développée avec Django et un déploiement sur Microsoft Azure via Terraform, notre solution est conviviale et évolutive.Découvrez notre projet ici :https://apipharma-app-service.azurewebsites.net/
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A collection of Data Science projects.
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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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A project to use machine learning to identify other measurements that might carry the same information as (harder to execute) measurements of spin correlations in top quark pairs produced at the LHC.
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A Machine Learning approaches to identify genetic variants associated with disease
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This git repository accompanies the work presented in the master's thesis titled "Context-based Tweet Engagement Prediction" written by Jovan Jeromela under the supervision of Assist.-Prof. Peter Knees in 2021 at TU Wien.
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Implemented Machine Learning methods by utilizing datasets and coding techniques to explore various ML topics. Through careful selection of datasets and coding in Python with libraries like numpy, pandas, and sklearn we addressed key questions and gained practical experience. This project enhanced my understanding of ML and strengthened my programming skills.
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Introduction to AI & Data Analysis: Classification of Iris-dataset with classic Perceptron Classification of MNIST-dataset with MLP and CNN
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My MSc thesis work. I essayed with a number of classifiers for two type of health-related time series: electrocardiogram and blood oxygen levels. The four approaches used on each type of signal were: (i) featured based approach, where integral and differential attributes where devised and used to classify the sets (ii) Direct Machine Learning application to the time series (Perceptron, Random Forest and others) (iii) 1D convolutional neural networks applied to the signals (iv) 2D convolutional neural networks applied to the signal spectrograms.
The thesis pdf file, included here, is written in Spanish.
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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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Attempted to create a model that could determine the genre of a song based off of features from Spotify's data.
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Questo progetto contiene al suo interno tutte le versioni create per lo studio condotto da Riccardo Romano e Dario Ceni sul dataset mics. Il tema di progetto: analisi esplorativa tramite ML su life satisfaction in MICS.
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Exact and differentiable spherical harmonic and Wigner transforms for TensorFlow
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IndyPy Talk 2023-02-14: Using AWS Artificial Intelligence services with Python https://www.meetup.com/indypy/events/289628031/
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