MP4 | Video: h264, 1920x1080 | 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 and want to deliver crucial data analysis insights to our audience.
K makes the data prep process efficient and easy. With K, 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 K a truly flexible and versatile tool.
In this course, we will learn how to use additional helpful K nodes not covered in the other two classes. Solve data cleaning challenges together for different datasets. Use pre-trained models in TensorFlow in K (involves Python coding).
Also, learn the fundamentals for NLP tasks (Natural Language Processing) in K using only K nodes (without any additional coding).
By the end of this course, you will be able to use K for data cleaning and data preparation without any code.
All the resources and support files for this course are available at
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