The platform has an exploration component that enables users to upload data, recommends correlated variables and creates comparisons. It allows users to receive answers to complicated questions depending on their data. It is a reporting tool, which supports report and dashboard development.
It has been stated by our IBM Watson assignment help providers that every component is used using a GUI or Graphical User Interface that reduces the requirement of advanced data science training. The platform is meant for making advanced analytics highly accessible to workers who have limited technical knowledge.
The cost depends on its version. You can get a free version that includes the capability of uploading spreadsheets, get insights, get visualizations, and create billboards.
What is IBM Watson?
IBM Watson is a supercomputer, which combines sophisticated analytical software and artificial intelligence or AI for optimal performance. The key components of IBM Watson include the following:
- Apache UIMA or Unstructured Information Management Architecture frameworks, infrastructure, and elements needed for analysing unstructured data.
- SUSE Enterprise Linux Server 11
- Apache’s Hadoop, Java-based and free programming framework, which supports processing of huge data sets in a computing environment.
- 15 terabytes of RAM
- 2,880 processor cores
- DeepQA software, designed to retrieve information that includes natural language processing and machine learning.
- 500 GB of information.
The applications of its cognitive computing technology are limitless. As the device can do complex analytics and text mining, it can support search engines or expert systems with abilities that are better than the existing ones.
IBM Watson and AI Applications
IBM has published a wide range of APIs or application program interfaces on the cloud that enables users to create their AI applications that use the core technology of Watson on its back end. APIs are there that support the development frameworks such as Python, Java, and others.
IBM has API connectors for deep learning algorithms that enable users in building applications for things such as image recognition, natural language processing, and tine analysis. API supports developing smart assistants with the use of Watson technology at its back end.