clabrugere
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Data Scientist with over 6 years of experience in data engineering, statistical analysis and machine learning, I thrive in applying cutting-edge tech to challenging business problems and build scalable data products leveraging state-of-the-art machine learning.
Implementation of SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption in Pytorch, a model learning a representation of tabular data using contrastive learning. It is inspire…
Implements the paper "Wukong: Towards a Scaling Law for Large-Scale Recommendation" from Meta.
Implements a LLM similar to Meta's Llama 2 from the ground up in PyTorch, for educational purposes.
Implementation of "Evidential Deep Learning to Quantify Classification Uncertainty" proposing a method to quantify uncertainty in a neural network.
Tensorflow implementation of three architectures for multi-task learning, a paradigm to learn different prediction tasks jointly using one model
Python 8
Example of a Dash application applied to e-commerce data to represent key metrics in the form of an interactive dashboard
