It is used to enhance user experience in an e-commerce setting. By leveraging data on user clicks, browsing behavior, and past interactions with the platform, we can create models that enable personalized product recommendations. These models can identify products that align with the customer's interests and preferences, thereby improving the chances of suggesting items that are highly relevant to the individual's needs.

I use IBM Watson Studio to analyze personal resumes. In general, we use the machine to analyze resumes.

It was used for some basic purposes because all I did was use Jupyter notebooks to run codes on the Snowflake environment. This was done by me at my previous job. I had just started using Jupyter notebooks to run Python codes on Snowflake data warehouses.

My primary use is to create a forecasting model for sales. I am doing automation from a supply chain point of view.

We mainly use it for our entire transformation logic. Everything that is in there, we store and process it in a similar fashion. We have globally rolled it out.

We use this product for every capability we have. It has greatly improved the performance because it is standardized across the company. Also, it will help us moving forward.

We are doing the cloud part of the IBM Watson Studio. The customer needed a marketing analytics solution. IBM Watson Studio is a very comprehensive suite of marketing solutions including AI and predictive analytics.

Our primary use for Watson Studio was to analyze the trans-video prints about the operation so they can get their own insight into how the public thinks about their corporation. Also, I analyzed resumes so the AI can generate the proper information for the resume.

I'm looking at data analytics for division making. In the working environment, I'm looking at how we can use the system to give insights based on company data relating to employees. 

The primary use case is an algorithm for our radar sensor for autonomous driving. We do use it in a cloud environment for our testing.

When there is more interference, the speed and efficiency of the algorithm become more important. This is where we have high hopes that this technique will help us. Not only in the current interference algorithm that we are working on, but in the future with things like object classification.

We use Watson Studio with an application we developed for restaurants on the Facebook Messenger platform using Chatbot. It contains many features like making orders and table reservations.

I primarily used the solution as an API. The solution was a deployed model and I was just installing the API, sending some data and returning some data from REST API. It was very easy to use.