Introduction to Machine Learning with KNIME
MP4 | Video: h264, 1280×720 | Audio: AAC, 48 KHz, 2 Ch | Duration: 1h 41m
Genre: eLearning | Language: English + Sub | Size: 322 MB
KNIME is an open-source workbench-style tool for predictive analytics and machine learning. It is highly compatible with numerous data science technologies, including R, Python, Scala, and Spark. With KNIME, you can produce solutions that are virtually self-documenting and ready for use. These reasons and more make KNIME one of the most popular and fastest-growing analytics platforms around. In this course, expert Keith McCormick shows how KNIME supports all the phases of the Cross Industry Standard Process for Data Mining (CRISP-DM) in one platform. Get up and running quickly-in 15 minutes or less-or stick around for the more in-depth training covering merging and aggregation, modeling, and data scoring. Plus, learn how to increase the power of KNIME with extensions and integrate R and Python.
Why use a workbench
Why choose KNIME?
Adding KNIME nodes with extensions
Exploring data statistically and visually
Merging and aggregating data in KNIME
Modeling in KNIME
Scoring new data
Combining KNIME with R and Python