ML & I
summary
An introductory overview of machine learning covering what ML is and common application areas such as assistants, image recognition (Google Assistant, Google Lens) and recommendation systems (Amazon). It contrasts ML engineering with conventional software engineering and discusses practical concerns around improving model accuracy and performance, drawing on experience from HyperScience.
AI-written summary · about
related talks
37mDemystifying machine learning – from developer to ML engineer
43mML application lifecycle
01h 24mWhat is Machine Learning?
01h 21mIntroduction to Machine Learning for Software Engineers
52mMachine learning: from practice to theory
49mUsing Machine Learning and Not Dying Trying
40mWhat is Machine Learning, and How Do I Get Started?
06mML for Systems and Systems for ML