Exploring machine learning with Watson Studio

November 12, 2019 devadvin

Machine learning is the baseline for domains like data science and artificial intelligence. The enormous amount of data generated every day reinforces the need for an automated approach toward dealing with data.

Watson Studio is a one-stop platform for all problems pertaining to data. It contains and environment and tools where data can be accessed and processed collaboratively. In Watson Studio, there are three ways to develop machine learning models:

  1. Machine learning model builder
  2. SPSS Modeler flow
  3. Jupyter Notebook

To get started with machine learning model builder, all you need to do after making a project in Watson Studio is click Add to Project, add a Watson Machine Learning Instance, and click Model Builder as the option while selecting the model type. You can select details for your model, such as:

  • Predicting column
  • Input column
  • The algorithm
  • The estimator
  • The data split.

This limits the coding expertise that you need. You can also run multiple algorithms that then appear along with metrics. You can then choose the model with most appropriate metrics.

New model window

For SPSS Modeler flow, you must add Modeler Flow from Add to Project. It lets you choose from various machine learning algorithms that are present as drag-and-drop icons. Various data preparation techniques are also available along with evaluation and statistics nodes that can be connected to the classifiers for determining whether it is working.

Nodes

Watson Studio can also be used to develop Jupyter Notebooks, where users interested in programming can code the machine learning models conventionally. This option is further used for programming in Python from scratch, or you can use a scikit-learn library for machine learning models. IBM Cloud gives you the chance to import your own notebooks from local systems, or you can fetch one from a URL.

New notebook window

To sum up in a nutshell, Watson Studio is an effective tool for developing machine learning models. You don’t need to have much programming experience in Python or R to start working on these models. Watson Studio accommodates users with different levels of expertise.

To learn more about Watson Studio, take a look at the Getting started with Watson Studio learning path.

Sana Mushtaq

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