Mastering Classification Algorithms for Machine Learning: Learn how to apply Classification algorithms for effective Machine Learning solutions

✍ Scribed by Partha Majumdar

Publisher: BPB Publications
Year: 2023
Tongue: English
Leaves: 380
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Recent combinations of semantic technology and artificial intelligence (AI) present new techniques to build intelligent systems that identify more precise results. Semantic AI in Knowledge Graphs locates itself at the forefront of this novel development, uncovering the role of machine learning to extend the knowledge graphs by graph mapping or corpus-based ontology learning.

Securing efficient results via the combination of symbolic AI and statistical AI such as entity extraction based on machine learning, text mining methods, semantic knowledge graphs, and related reasoning power, this book is the first of its kind to explore semantic AI and knowledge graphs. A range of topics are covered, from neuro-symbolic AI, explainable AI and deep learning to knowledge discovery and mining, and knowledge representation and reasoning.

A trailblazing exploration of semantic AI in knowledge graphs, this book is a significant contribution to both researchers in the field of AI and data mining as well as beginner academicians.

✦ Table of Contents

Introduction to Machine Learning
Naïve Bayes Algorithm
K-Nearest Neighbor Algorithm
Logistic Regression
Decision Tree Algorithm
Ensemble Models
Random Forest Algorithm
Boosting Algorithm
Annexure 1: Jupyter Notebook
Annexure 2: Python
Annexure 3: Singular Value Decomposition
Annexure 4: Preprocessing Textual Data
Annexure 5: Stemming and Lamentation
Annexure 6: Vectorizers
Annexure 7: Encoders
Annexure 8: Entropy

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