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KNIME for Data Science and Data Cleaning [Video]

KNIME for Data Science and Data Cleaning: Perform data science and data cleaning with KNIME by solving data cleaning challenges together

Dan We

By Dan We

€101.99

Video Aug 2021 2 hours 49 minutes 1st Edition

Renews at €18.99p/m

Dan We

By Dan We

€101.99

Video Aug 2021 2 hours 49 minutes 1st Edition

Renews at €18.99p/m

Renews at €18.99p/m

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Download this video in MP4 format

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Key benefits

No coding required
Solve data cleaning challenges together and enhance your basic KNIME skills
Learn the fundamentals for NLP tasks in KNIME using only KNIME nodes

Description

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

What you will learn

How to use TensorFlow in KNIME
How to do data science in KNIME with and without coding
How to solve data cleaning and data preparation challenges
How to replace Excel and start KNIME for ETL and data cleaning issues
Examples of data science machine learning workflows with KNIME

What do you get with a video?

Download this video in MP4 format

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Product Details

Publication date : Aug 24, 2021

Length 2 hours 49 minutes

Edition : 1st Edition

Language : English

ISBN-13 : 9781801071413

Category :

Concepts :

Tools :

Knime (Beginner)

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Table of Contents

2 Chapters

1. Introduction

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

2. Older Videos KNIME Version Before 4.3

Copying or Moving Files with KNIME

Reading Multiple Excel Files - Benefits of Loops

Excel Files with Different Table Structure in KNIME

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KNIME for Data Science and Data Cleaning

KNIME for Data Science and Data Cleaning

Aug 2021 2h 49m

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€101.99

About the author

Dan We

Dan We

Dan We is a 32-year-old entrepreneur, data scientist, and data analytics/visual analytics consultant. He holds a master’s degree and is certified in Power BI as a qualified associate in Tableau. He is currently working in business intelligence and helps major companies get key insights from their data in order to deliver long-term growth and outpace their competitors. He is committed to supporting other people by offering them educational services to help them accomplish their goals and become the best in their profession or explore a new career path.

See other products by Dan We

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