Machine Learning has been an integral part of the technological world today. The ability to understand a particular pattern and be able to predict or remember is intriguing. Furthermore extending cognitive abilities to a machine creates an ocean of opportunities. This is harnessed by some of the biggest multinational corporations (MNC) to mine the power of technology and provide better customer service.
Let us take the example of IBM. One of the technological marvels of the organization is the IBM Watson. The supercomputer has proven to be a frontrunner in the field of Artificial Intelligence and the IBM Watson Machine Learning helps data scientists and developers accelerate AI and ML deployment. It also helps businesses simplify and harness AI at scale across any cloud.
Now the question stands at, why Watson? The Watson ML helps in deploying models built with Watson studio, dynamically retrain models and automatically generate APIs. Moreover, it accelerates the time to value of a model. This has ensured 80% of AI pioneers investing in the process to train algorithms.
Some of the distinguishing features of IBM Watson are as follows:
AutoAI helps in gaining consistency and repeatability of end-to-end AI life cycle management
A Machine Learning framework is used for saving, deploying and visioning models and for deployment of infrastructure management.
A user-friendly readable UI provides a wonderful experience to automate data prep, advance data refineability and model explainability.
Another major advantage is the ability to deploy the model at scale over a cloud platform. Major data science tools from open source, IBM SPSS Modeler and Watson Studio can be used.
This can be used to train models, for example, to identify images or color or even sort images based on certain parameters.