No code ML is an approach to build an ml based models without doing any heavy data work or ml coding .
No code ML platforms designed for business users or analysts with the domain knowledge of the overall workflow but thus business users have less or no coding experience.
AWS SageMaker Canvas is No code ML platform.
before you go to AWS SageMaker Canvas .. you must make sure you know at high level how the ML workflow looks likes
there is 4 main phases :
phase-1 : gathering , ingestion , extraction of data
phase-2 : data exploring , understanding , cleaning , transforming and pre-processing ( why i put thus in one phase its coz the more you understand the data the better you can pre-process it and feature engineer it )
phase-3 : modeling ( training and validation )
phase-4 : serving and monitoring
according to above let see simple ML project story
a simple ML project story you team (jason is data eng , ali is data scientist , jack is ml researcher , mamon is ml engineer )
jason setup data pipeline that start by collecting and storing and organizing cataloging the data and make it ready for consuming by others, ali gathered some data from data from sources that jason already maintain , and now ali explored data and you clean it and make some preprocessing and feature engineering on the data and delivered it to jack.
jack started to split data and do modeling and training and benchmarking now jack deliver a trained model with it artifact to mamon.
mamon validate the model build the serving service and push the model to production.
now imagine that with AWS SageMaker Canvas you can do (ali , jack ) work with simple clicks and no deep coding knowledge.
let see how