Artificial intelligence has been growing exponentially since its emergence, and with the idea that you learn a little more about this topic, we prepared a varied collection of free machine learning books in PDF format.
Machine Learning is a branch of Artificial Intelligence, which through algorithms provides computers with the ability to detect and identify patterns within massive data, to generate forecasts or predictive analysis.
This AI discipline is considered a scientific field and works with information in the form of words, numbers, statistics, and images, among many others.
For the development of these algorithms, various programming languages are used such as Python, C++, R, Java, JavaScript, C#, Julia, TypeScript, Shell, and Scala.
You can immerse yourself in this subject of great interest and current affairs, reading any of our more than 70 materials, including books and free articles on machine learning in PDF format.
Machine Learning Books
Machine learning - The power and promise of computers that learn by example
Royal Society
Artificial Intelligence and Machine Learning Approaches in Digital Education - A Systematic Revision
Hussan Munir, Bahtijar Vogel and Andreas Jacobsson
Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions
Raffaele Cioffi, Marta Travaglioni, Giuseppina Piscitelli, Antonella Petrillo and Fabio De Felice
Best Practices for Machine Learning Applications
Brett Wujek, Patrick Hall, and Funda Gunes
The fundamentals of machine learning
Jay Wilpon, David Thomson, Srinivas Bangalore, Patrick Haffner and Michael Johnston
An Introduction to Machine Learning
Solveig Badillo, Balazs Banfai, Fabian Birzele and others
How Artificial Intelligence, Machine Learning and Deep Learning are Radically Different? (Article)
Tanya Tiwari, Tanuj Tiwari and Sanjay Tiwari
Machine Learning in Artificial Intelligence - Towards a Common Understanding (Article)
Niklas Kühl, Marc Goutier, Robin Hirt, Gerhard Satzger
Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature (Article)
Andreas K Triantafyllidis and Athanasios Tsanas
Algorithms in Machine Learning Books
In the world of machine learning, algorithms are an essential part of the machine learning process, and understanding them can be critical to developing innovative solutions in different areas.
Algorithms in machine learning are a series of defined steps that allow machines to learn from data and improve their performance over time.
If you are interested in learning more about this topic, we invite you to explore our selection of free books and articles on machine learning algorithms.
Clustering Algorithms: A Comparative Approach
Mayra Z. Rodriguez, Cesar H. Comin, Dalcimar Casanova and others
Dbscan - Fast Density-based Clustering with R
Michael Hahsler, Matthew Piekenbrock and Derek Doran
Extension of DBSCAN in Online Clustering: An Approach Based on Three-Layer Granular Models
Xinhui Zhang, Xun Shen and Tinghui Ouyang
A review of Machine Learning (ML) algorithms used for modeling travel mode choice
Pineda-Jaramillo and Juan D
A Taxonomy of Machine Learning Clustering Algorithms, Challenges, and Future Realms
Shahneela Pitafi, Toni Anwar and Zubair Sharif
DBSCAN: A simple fast DBSCAN algorithm for big data
Shaoyuan Weng, Jin Gou and Zongwen Fan
Implementation of Decision Tree Algorithm to Classify Knowledge Quality in a Knowledge Intensive System
Casper Kaun, N.Z Jhanjhi, Wei Wei Goh and Sanath Sukumaran
Supervised Machine Learning Algorithms - Classification and Comparison (Article)
Osisanwo F.Y, Akinsola J.E.T, Awodele O and others
Random Forest Classifiers :A Survey and Future Research Directions (Article)
Vrushali Y Kulkarni and Pradeep K Sinha
Supervised Learning Books
Supervised learning is one of the most popular and widely used techniques in the field of Machine Learning. It is a type of learning in which an algorithm is trained using a labeled data set to learn to make accurate predictions or classifications.
Supervised learning is used in a wide variety of Machine Learning applications, such as image classification, email spam detection, fraud detection in financial transactions, and many others.
Learn more about this powerful and versatile technique with the following free supervised learning books and articles in PDF format.
Supervised Learning Techniques - A comparison of the Random Forest and the Support Vector Machine
Jonni Fidler Dennis and Lukas Arnroth
Supervised Machine Learning Techniques: An Overview with Applications to Banking
Linwei Hu, Jie Chen, Joel Vaughan, Hanyu Yang and others
Unsupervised Learning Books
Unsupervised learning is another essential technique used in Machine Learning. Unlike supervised learning, where the algorithm is trained using a labeled data set, in unsupervised learning the algorithm is prepared using an unlabeled data set.
In unsupervised learning, the algorithm is responsible for finding patterns in the input data on its own, without being told what to look for. This technique is especially useful in situations where there is no labeled training data set available.
This technique is used in a wide variety of Machine Learning applications, such as customer segmentation, data clustering, anomaly detection, and many others. You can learn a little more with the following unsupervised learning books and articles in PDF format.
Discovery of Course Success Using Unsupervised Machine Learning Algorithms
Emre CAM and Muhammet Esat OZDAG
Deep Learning Books
Deep learning is a machine learning technique that uses artificial neural networks to learn from large data sets and improve their ability to perform complex tasks.
It has become increasingly popular in recent years due to its ability to tackle complex problems in different areas, from medicine to robotics.
It has also enabled significant advances in areas such as speech recognition and computer vision. You can learn more about this topic with the following books and articles on deep learning.
Machine learning and deep learning (Article)
Christian Janiesch, Patrick Zschech and Kai Heinrich
Machine Learning and Database Books
Machine learning and databases are two closely related topics. In simple terms, databases are an essential tool for storing and organizing large data sets, while Machine Learning is a technique for analyzing and extracting useful information from that data.
Together, machine learning and databases are essential for processing and analyzing large data sets. For example, machine learning algorithms can be used to analyze data stored in a database and provide useful information to users.
In addition, databases can be used to store and organize the data needed to train machine learning algorithms. Learn more about this interesting relationship with the following books and articles on machine learning and databases.
Data Science and Machine Learning
Dirk P. Kroese, Zdravko I. Botev, Thomas Taimre and Radislav Vaisman
Machine Learning with Big Data - Challenges and Approaches
Alexandra L’Heureux, Katarina Grolinger, Hany F. ElYamany, Miriam A. M. Capretz
A review on the significance of machine learning for data analysis in big data
Vishnu Vandana Kolisetty and Dharmendra Singh Rajput
UDO: Universal Database Optimization using Reinforcement Learning
Junxiong Wang, Immanuel Trummer and Debabrota Basu
Neural Networks Books
Neural networks are computational systems that are inspired by the workings of the human brain and are used to learn from large data sets and perform complex tasks in an automated manner.
They are commonly used in computer vision, natural language processing, and robotics. In addition, deep neural networks have enabled significant advances in the field of deep learning.
If you would like to learn more, we invite you to take a look at the following books and articles on neural networks that we have located for you in PDF format.
Here ends our selection of free Machine Learning Books in PDF format. We hope you liked it and already have your next book!
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