Book Image

Data Analytics Made Easy

By : Andrea De Mauro
4 (1)
Book Image

Data Analytics Made Easy

4 (1)
By: Andrea De Mauro

Overview of this book

Data Analytics Made Easy is an accessible beginner’s guide for anyone working with data. The book interweaves four key elements: Data visualizations and storytelling – Tired of people not listening to you and ignoring your results? Don’t worry; chapters 7 and 8 show you how to enhance your presentations and engage with your managers and co-workers. Learn to create focused content with a well-structured story behind it to captivate your audience. Automating your data workflows – Improve your productivity by automating your data analysis. This book introduces you to the open-source platform, KNIME Analytics Platform. You’ll see how to use this no-code and free-to-use software to create a KNIME workflow of your data processes just by clicking and dragging components. Machine learning – Data Analytics Made Easy describes popular machine learning approaches in a simplified and visual way before implementing these machine learning models using KNIME. You’ll not only be able to understand data scientists’ machine learning models; you’ll be able to challenge them and build your own. Creating interactive dashboards – Follow the book’s simple methodology to create professional-looking dashboards using Microsoft Power BI, giving users the capability to slice and dice data and drill down into the results.
Table of Contents (14 chapters)
10
And now?
12
Other Books You May Enjoy
13
Index

Chapter 4

  • For a general introduction on topic modeling, see https://monkeylearn.com/blog/introduction-to-topic-modeling. In particular, LDA is implemented in KNIME within the Topic Extractor (Parallel LDA) node, which is part of the KNIME Textprocessing extension.
  • The following paper reveals the challenges related to the implementation of reinforcement learning in real-world problems: Dulac-Arnold, G., Mankowitz, D., & Hester, T. "Challenges of real-world reinforcement learning." arXiv preprint arXiv:1904.12901 (2019), https://arxiv.org/pdf/1904.12901.pdf.
  • One of the most promising types of machine learning algorithms is neural networks. They make a machine learning subdiscipline by itself, called Deep Learning. To get started with deep learning in KNIME, I recommend reading Melcher, K., Silipo, R., Codeless Deep Learning with KNIME: Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform. Packt Publishing Ltd, 2020...