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IBM Data Science Experience (DSX)

https://datascience.ibm.com/

IBM Data Science Experience (DSX) is an enterprise platform for data science and machine learning.

  1. DSX provides a comprehensive collaborative workbench for your whole data science team including data engineers, app developers and data scientists to create and operate machine learning systems at scale.

  2. DSX covers the complete end to end machine learning workflow from model development to model deployment and management.

  3. DSX is offered on public cloud, private cloud and mainframe, and provides fit-for-purpose deployment options so enterprise customers can bring machine learning capabilities to where their data resides.

IBM Data Science Experience Components:

Projects

Projects are where you work with data assets, notebooks, dashboards, flows and other resources.

Try it yourself:

  • Create project
  • Add collaborators
  • Add data asset (Over 30 Connections to connect to other IBM and 3rd party services)

Catalog

Catalog is a searchable index of all structured and unstructured data living in existing systems and cloud platforms

Try it yourself:

  • Create a new catalog
  • Upload a file, add tags
  • Add the file to a project

Notebooks

Notebook is an interactive web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Notebook is where you can work with Python, R, and Scala code along with Spark to create document-like analytics.

Try it yourself:

  • Create a new notebook
  • Import a notebook
  • Run notebooks

SPSS Modeler Flows

SPSS Modeler Flow is a graphical representation of data, by using the Flow Editor to prepare or shape data, train or deploy a model, or transform data and export it back to a database table or file in object storage. Modeler offers modeling techniques, such as prediction, classification, segmentation, and association detection algorithms using SPSS Modeler or Scala Spark 2.0 Runtimes.

Model Builder

Model builder uses the power of Watson Machine Learning to automatically prepare data and build models.* The model builder in manual model allows you to select and evaluate multiple machine learning models

RStudio

R is a programming language and software environment for statistical computing, graphical representation, and reporting. RStudio is a free and open-source integrated development environment (IDE) for R.

Data Refiner (Beta)

Data Refiner is where you can prepare, cleanse, and process data

  • Filter
  • Convert data type
  • Visualize data
  • Refine data and show resulting Data Flow