Read Deep Learning with Python [1]. It's ok not to understand everything, but doing the labs will be invaluable.
That book should set you up with the fundamentals. Pytorch is the defacto standard right now for training; during deployment you will use whatever your deployment setup allows (e.g. embedded devices typically have their own inference frameworks).
Python is the lingua franca for anything in machine learning, but other languages are used where necessary for performance or for ecosystem benefits.
That book should set you up with the fundamentals. Pytorch is the defacto standard right now for training; during deployment you will use whatever your deployment setup allows (e.g. embedded devices typically have their own inference frameworks).
Python is the lingua franca for anything in machine learning, but other languages are used where necessary for performance or for ecosystem benefits.
[1]: https://www.manning.com/books/deep-learning-with-python