Description
This book guides professionals and students from various backgrounds to use machine learning in their own fields with low-code platform KNIME and without coding. Many people from various industries need use machine learning to solve problems in their own domains. However, machine learning is often viewed as the domain of programmers, especially for those who are familiar with Python. It is too hard for people from different backgrounds to learn Python to use machine learning. KNIME, the low-code platform, comes to help. KNIME helps people use machine learning in an intuitive environment, enabling everyone to focus on what to do instead of how to do.
This book helps the readers gain an intuitive understanding of the basic concepts of machine learning through illustrations to practice machine learning in their respective fields. The author provides a practical guide on how to participate in Kaggle completions with KNIME to practice machine learning techniques.
Table of Contents
Chapter 1 Overview of Artificial Intelligence and Machine Learning.- Chapter 2 Basic Knowledge of Machine Learning.- Chapter 3 Linear Regression.- Chapter 4 Logistic Regression.- Chapter 5 Model Optimization.- Chapter 6 Support Vector Machine.- Chapter 7 Decision Tree.- Chapter 8 Understanding of Decision Tree.- Chapter 9 Bayesian Analysis.- Chapter 10 Deep Learning.
