Udemy - KNIME for Data Science and Data Cleaning

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Udemy - KNIME for Data Science and Data Cleaning (Size: 2.2 GB)
  01-Welcome to KNIME.mp4 10.6 MB
  02-Copying or Moving Files with KNIME.mp4 28.4 MB
  03-Reading multiple Excel files - Potential Errors and Solutions.mp4 120.9 MB
  04-Reading Multiple Excel Files - Benefits of Loops.mp4 145.4 MB
  05-Excel Files with Different Table Structures in KNIME.mp4 122.8 MB
  06-Useful Nodes - Column Aggregations.mp4 197.4 MB
  07-Countries - Data Cleaning Challenge.mp4 113.9 MB
  08-Merge Table Challenge in KNIME.mp4 94.7 MB
  09-A JSON File Challenge in KNIME.mp4 190.9 MB
  10-Create the Neural Network h5 Model File to be Used in KNIME.mp4 92.9 MB
  11-Mismatching Addresses - Introduction to Similarity Search in KNIME.mp4 103 MB
  12-TensorFlow Neural Network Regression Implementation in KNIME.mp4 153.1 MB
  13-Transfer Learning in KNIME Using Python Scripts.mp4 34.7 MB
  14-Introduction to NLP in KNIME Part 1.mp4 142.5 MB
  15-NLP in KNIME Part 2 - Data Preprocessing and Cleaning.mp4 146.5 MB
  16-NLP in KNIME Part 3 - Bag of Words and Document Vector.mp4 149.8 MB
  17-NLP in KNIME - Choose ML Algorithm and Score Our Model.mp4 123.9 MB
  18-Congratulations.mp4 4.4 MB
  19-Copying or Moving Files with KNIME.mp4 61 MB
  20-Reading Multiple Excel Files - Benefits of Loops.mp4 115.4 MB
  21-Excel Files with Different Table Structure in KNIME.mp4 74.6 MB
  Bonus Resources.txt 307.2 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 23 total files

Description


KNIME for Data Science and Data Cleaning



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 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.

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