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This guide explores building a scalable training pipeline using PyTorch Lightning and LightningCLI. It covers handling dataset preparation, where different transformations for training and validation are applied. The post details how Lightning organizes code into data and model modules, streamlining training but complicating parameter sharing. By using LightningCLI and link_arguments, key parameters are passed between modules. Based on the discussed aspects a final blueprint is proposed.

Our new paper titled 'Hologram Noise Model for Data Augmentation and Deep Learning' has been published in MDPI Sensors.

Explore the transformative world of machine learning, where computers learn from data, uncover patterns, and make decisions without explicit programming. Discover the core components of machine learning and its historical evolution.

This year I would like to write an article series about Marcos Lopez de Padro's Advances in Financial Machine learning book and review articles and books about the topic of machine learning in finance.

In this post, I present my second big project, now in the field of computer vision and remote Photoplethysmography (rPPG).