- Stockholm
- in/neginebrahimi
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ml-federated-learning
ml-federated-learning PublicFederated Learning project using the Flower (FLWR) framework and PyTorch on CIFAR-10, demonstrating privacy-preserving distributed model training with multiple simulated clients.
Python 1
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RNN_TimeSeries_Project
RNN_TimeSeries_Project PublicDeep learning project focusing on time series prediction and classification using RNN, LSTM, and GRU models.
Python 1
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Transformers_BERT_NLP
Transformers_BERT_NLP PublicDeep learning project focusing on transformer-based models (BERT) for NLP tasks, including fine-tuning, tokenization, and evaluation using PyTorch and Hugging Face.
Python 1
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ConvolutionalNeuralNetworks-CNN
ConvolutionalNeuralNetworks-CNN PublicDeep learning lab focusing on image classification using fully connected and convolutional neural networks (CNN) in PyTorch, applied to the CIFAR-10 dataset.
Python 1
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TrainingNeuralNetworks-NNs
TrainingNeuralNetworks-NNs PublicDeep learning project on training neural networks using PyTorch, exploring optimizers, schedulers, and performance improvements on the Fashion-MNIST dataset.
Python 1
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Regression_and_Classification
Regression_and_Classification PublicMachine learning project focused on regression and classification tasks, including data preprocessing, feature engineering, and supervised learning using scikit-learn.
Jupyter Notebook 1
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