MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
2021 | ISBN: 9781801071413 | English
Duration: 21 Lessons (2h 49m) | Size: 1.22 GB
Data cleaning is always a big hassle, especially if we are short on time and want to deliver crucial data analysis insights to our audience. KNIME makes the data prep process efficient and easy. With KNIME, you can use the easy-to-use drag-and-drop interface, if you are not an experienced coder. But if you know how to work with languages such as R, Python, or Java, you can use them as well. This makes KNIME a truly flexible and versatile tool.
In this course, we will learn how to use additional helpful KNIME nodes not covered in the other two classes. Solve data cleaning challenges together for different datasets. Use pre-trained models in TensorFlow in KNIME (involves Python coding).
Also, learn the fundamentals for NLP tasks (Natural Language Processing) in KNIME using only KNIME nodes (without any additional coding).
By the end of this course, you will be able to use KNIME for data cleaning and data preparation without any code.
All the resources and support files for this course are available at
https://github.com/PacktPublishing/KNIME-for-Data-Science-and-Data-Cleaning
