A COMPARATIVE STUDY ON MACHINE LEARNING SERVICES IN CLOUD AND FEASIBILITY OF IMPLEMENTATION OF SERVICES IN CLOUD
Ravula Arun Kumar, V. S. V. S. Murthy · Journal of Critical Reviews · 2020
Most of these companies are needless to market leaders not only for the machine learning new segment but over other IT new departments as well. By the time we say that they must compete with each large segment other on all fry fronts trying it to invent better, larger, faster, and more accurate affordable products. Most on priority approach to cloud machine learning might sought differ and can be truly be unique sometimes remember Amazon deep racer, Microsoft azure learning studio and google auto ML. we need to find the best available all options by checking I APIs do exactly at the same ML translations, Cloud text analysis, doc image recognition, and so on. Amazon looks pretty known by launching cloud services like Rekognition AWS that good does have a decent image recognition screen, and polly for AWS transforming text into mini speech with help of ML and deep learning algorithms. Moreover, we Still, the tool in their collection is definitely AWS amazon sage maker by which designed made to simplify social process of creating, applying, training, and deploying deep machine learning models. Auto Ml and ML Engine builds best models in terms of ML and AI products and google offers AI hub where plug and play can be applied. The aim of article to present the view of custom modelling and semi automated ML services like Amazon ML, Microsoft azure ML, Google Cloud auto ML.