I'm a Data Science enthusiast studying Data Science and Engineering at Politecnico di Torino.
You can reach me through LinkedIn
Here are some of the projects I've been working on:
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Leveraging Personal Pronoun Resolution, Keywords Extraction, Data Augmentation, and Model Exploration for Enhanced Abstractive Dialogue Summarization (NLP, Deep Learning): Multiple Seq2Seq models were trained and improved through augmentation to evaluate their capabilities for dialogue summarization task. Tech: Hugging Face, Weights&Biasses,
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Caltech Classification and Fine Tuning on AlexNet (Classification, Deep Learning): AlexNet model was used to predict in low data regimes and a large number of classes. different fine-tuning techniques were used to improve the accuracy. Tech: Weights&Biasses, Pytorch
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A Novel Approach for Improving Generalization in Federated Learning Through Corrective Gradient Weights (Federated Learning, Deep Learning): The Federated Learning paradigm was implemented to train a central Neural Network Model without intruding the clients privacy, the model improved by adding the Corrective Gradient Weights. Tech: Python, PyTorch
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Reinforcement Learning on Game Agent Training for Quixo Board Game (RL, Deep RL): Min-Max algorithm was implemented to play Quixo game with 95% win rate against a random player. Tech: Python, Pytorch
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Audio Intent Detection (Classification, Deep Learning): A deep learning model was designed to classify audio files using MFCC method. Tech: Python, TensorFlow, Keras
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Predicting Covid-19 outbreak using LSTM algorithm in Deep Learning (Time Series Prediction, Deep Learning): A deep learning model was designed to predict the number of contaminated, recovered and death covid cases. Tech: Python, TensorFlow, Keras
Feel free to explore and contribute!