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Machine Learning
Welcome to the World of Machine Learning
Machine Learning, a subset of artificial intelligence, focuses on the development of algorithms that enable computers to learn from and act on data. It's a rapidly evolving field that is transforming industries worldwide. At Refhub.ir, we offer a comprehensive collection of machine learning books to cater to everyone from beginners to seasoned professionals.
Why Explore Machine Learning Books?
Described as one of the most exciting technologies of our time, Machine Learning is at the forefront of technological evolution. Reading books in this field not only equips you with foundational knowledge but also keeps you updated with the latest advancements and methodologies. Our carefully curated selection of books covers a wide range of topics including predictive analytics, neural networks, deep learning, and natural language processing.
Books for Every Level
Whether you're just starting out or looking to deepen your understanding of complex algorithms, our Machine Learning category has something for you.
Beginners can dive into introductory books that break down the basics of ML models, data processing, and essential algorithms in an easy-to-understand manner. Advanced learners and specialists will appreciate technical books that delve into sophisticated machine learning models and techniques, practical case studies, and real-world applications.
Key Topics Covered
Our collection focuses on both foundational concepts and cutting-edge developments in Machine Learning.
- Supervised and Unsupervised Learning
- Neural Networks and Deep Learning
- Data Preprocessing Techniques
- Reinforcement Learning
- Machine Learning for Big Data
- Natural Language Processing and Computer Vision
- Ethical Considerations and Bias in Machine Learning
Benefits of Learning Machine Learning
Mastering machine learning can unlock new career opportunities and enhance your data-driven decision-making skills. Learning from our selection of books will help you to:
- Understand and apply machine learning algorithms to solve real-world problems.
- Develop and deploy ML models effectively.
- Harness the power of data for strategic insights.
- Stay updated with the latest technological trends and innovations.
Enhance Your Learning Experience
Our online platform is designed to enhance your book-browsing experience with user-friendly features and intuitive categorization. With dedicated support and periodic updates to our catalog, Refhub.ir is your ideal partner in mastering machine learning.
Stay Ahead in Your Field
The field of Machine Learning is rapidly evolving, and staying ahead of the curve is essential. Whether your interest lies in theoretical concepts or practical applications, our diverse selection of books offers the resources you need to excel.
Embrace the power of learning and equip yourself with the knowledge to thrive in today's digital world. Explore our Machine Learning category and make your learning journey both insightful and enriching.
Books
608 resultsMastering Machine Learning on AWS: Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow
Dr. Saket S.R. Mengle,Maximo Gurmendez
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
Armando Fandango
Learning Ray: Flexible Distributed Python for Machine Learning
Max Pumperla,Edward Oakes,Richard Liaw
Principles of Data Mining and Knowledge Discovery: 5th European Conference, PKDD 2001, Freiburg, Germany, September 3–5, 2001 Proceedings
Jafar Adibi,Wei-Min Shen (auth.),Luc De Raedt,Arno Siebes (eds.)
PyTorch Deep Learning Hands-On: Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily
Sherin Thomas,Sudhanshu Passi
Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn and TensorFlow
Sebastian Raschka,Vahid Mirjalili
Mastering Machine Learning with scikit-learn: Apply effective learning algorithms to real-world problems using scikit-learn
Gavin Hackeling
Applied Deep Learning with Keras: Solve complex real-life problems with the simplicity of Keras
Bhagwat, Ritesh;Abdolahnejad, Mahla;Moocarme, Matthew
Hands-On Machine Learning with ML.NET: Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#
Jarred Capellman
Mastering Classification Algorithms for Machine Learning: Learn how to apply Classification algorithms for effective Machine Learning solutions
Partha Majumdar
Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale
Lakshmanan, Valliappa;Tigani, Jordan
Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2023
Suchismita Chinara,Asis Kumar Tripathy,Kuan-Ching Li,Jyoti Prakash Sahoo,Alekha Kumar Mishra
Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning (2nd Ed, Release 4)
Chris Albon
Mastering Machine Learning on AWS: Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow
Dr. Saket S.R. Mengle, Maximo Gurmendez
Hands-on Machine Learning with Python: Implement Neural Network Solutions with Scikit-learn and PyTorch
A. Pajankar, A. Joshi
Journal of Machine Learning Research
Frezza-Buet, Hervé (author);Geist, Matthieu (author)
Mastering Apache Spark 2.x Scale your machine learning and deep learning systems with SparkML, DeepLearning4j and H2O
Romeo Kienzler
Adversarial Machine Learning: Attack Surfaces, Defence Mechanisms, Learning Theories in Artificial Intelligence
Aneesh Sreevallabh Chivukula,Xinghao Yang,Bo Liu,Wei Liu,Wanlei Zhou
Probabilistic Machine Learning: Advanced Topics (Adaptive Computation and Machine Learning series)
Kevin P. Murphy
Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python
Moolayil, Jojo
Mastering PyTorch: Create and deploy deep learning models from CNNs to multimodal models, LLMs and beyond, 2nd Edition
Ashish Ranjan Jha
Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (4 volumes)
Cheng Few Lee (editor), John C. Lee (editor)
Recommender Systems: An Introduction
Dietmar Jannach,Markus Zanker,Alexander Felfernig,Gerhard Friedrich
Automated Machine Learning with Microsoft Azure: Build highly accurate and scalable end-to-end AI solutions with Azure AutoML
Dennis Michael Sawyers
Novel Financial Applications of Machine Learning and Deep Learning: Algorithms, Product Modeling, and Applications
Mohammad Zoynul Abedin,Petr Hajek
R DEEP LEARNING PROJECTS : master the techniques to train and deploy neural networks in r
LIU,YUXI (HAYDEN). MALDONADO PABLO
Machine Learning and Knowledge Extraction
Baimukashev, Daulet; Zhilisbayev, Alikhan; Kuzdeuov, Askat; Oleinikov, Artemiy; Fadeyev, Denis; Makhataeva, Zhanat;[...]Varol, Huseyin Atakan
Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python
Akshay Kulkarni,Adarsha Shivananda
State-of-the-Art Deep Learning Models in TensorFlow: Modern Machine Learning in the Google Colab Ecosystem
David Paper (auth.)
Intelligent Projects Using Python: 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras
Santanu Pattanayak
Machine Learning with Qlik Sense: Utilize different machine learning models in practical use cases by leveraging Qlik Sense
Hannu Ranta
Fundamentals of Machine Learning for Predictive Data Analytics : Algorithms, Worked Examples, and Case Studies
John D. Kelleher; Brian Mac Namee; Aoife D’Arcy