Learn how to design, implement, test, and configure canonical logging across microservices using Python and Tornado web framework.
Design API data model for communicating with the service, object model for the application logic, and physical storage model for persisting the data.
Learn to implement Tornado HTTP endpoints as a layer on business logic. Tune it to assist debugging, and write unit and integration tests.
Scalable and efficient data pipelines are as important for the success of data science and machine learning as reliable supply lines are for winning a war.
Tornado, with AsyncIO APIs, is an efficient framework for building IO-bound Python microservices. Learn key concepts. Set up lint, test, code coverage.
Google Speech-to-Text, Amazon Transcribe, Microsoft Azure Speech, Watson, Nuance, CMU Sphinx, Kaldi, DeepSpeech, Facebook wav2letter.
Learn to build audio transcriber for voice applications using PyAudio and Mozilla DeepSpeech speech-to-text Automated Speech Recognition (ASR) Python API.
Introduction to data science, machine learning, and deep learning for software engineers and developers, with curated online resources.