Take your familiarity with making ML models in a sandbox to that of the rich ecosystem of AWS. Leverage this large number of tutorials and resources from the AWS Developer Center.
Not ML-specific, but ML-adjacent: you might find yourself needing more training and education on System Design in the scenario where you are familiar with building ML models but want to be more involved in deploying them. Especially if you are migrating from traditional mechanical/aerospace disciplines into software developer roles.
Train and fine-tune models, manage models from experimentation to production, and track and evaluate LLM applications.
Intended to guide learners to more theoretical and advanced machine learning content. You will see that many of the resources use TensorFlow, however, the knowledge is transferable to other ML frameworks.
Want a more intuitive and deeper understanding of some of the trickier concepts as you continue to develop your ML proficiency? 3Blue1Brown is a notoriously great resource that uses animations to help educate. Broad topics covered in math, or adjacent fields like physics and computer science.
This book is selectively focused on deep learning, but goes into diverse related topics, such as linear algebra, calculus, probabilities, optimization, signal processing, programming, algorithmics, and high-performance computing
