![KNIME for Data Science and Data Cleaning [Video]](https://static.packt-cdn.com/products/9781801071413/cover/smaller)
KNIME for Data Science and Data Cleaning [Video]
- FREE Subscription Read for free
- $134.99 Video Buy
- $12.99 Video + Subscription Buy
-
What do you get with a Packt Subscription?
- Instant access to this title and 7,500+ eBooks & Videos
- Constantly updated with 100+ new titles each month
- Breadth and depth in over 1,000+ technologies
-
Free ChapterIntroduction
- Welcome to KNIME
- Copying or Moving Files with KNIME
- Reading multiple Excel files - Potential Errors and Solutions
- Reading Multiple Excel Files - Benefits of Loops
- Excel Files with Different Table Structures in KNIME
- Useful Nodes - Column Aggregations
- Countries - Data Cleaning Challenge
- Merge Table Challenge in KNIME
- A JSON File Challenge in KNIME
- Create the Neural Network h5 Model File to be Used in KNIME
- Mismatching Addresses - Introduction to Similarity Search in KNIME
- TensorFlow Neural Network Regression Implementation in KNIME
- Transfer Learning in KNIME Using Python Scripts
- Introduction to NLP in KNIME Part 1
- NLP in KNIME Part 2 - Data Preprocessing and Cleaning
- NLP in KNIME Part 3 - Bag of Words and Document Vector
- NLP in KNIME - Choose ML Algorithm and Score Our Model
- Congratulations
-
Older Videos KNIME Version Before 4.3
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
- Publication date:
- August 2021
- Publisher
- Packt
- Duration
- 2 hours 49 minutes
- ISBN
- 9781801071413
Download code from GitHub