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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 resultsApplied Deep Learning and Computer Vision for Self-Driving Cars: Build autonomous vehicles using deep neural networks and behavior-cloning techniques
Ranjan,Sumit,Senthamilarasu,Dr. S.
Mastering Machine Learning with scikit-learn: Apply effective learning algorithms to real-world problems using scikit-learn
Gavin Hackeling
Mastering Classification Algorithms for Machine Learning: Learn how to apply Classification algorithms for effective Machine Learning solutions
Partha Majumdar
Nature Inspired Optimization for Electrical Power System (Algorithms for Intelligent Systems)
Manjaree Pandit (editor),Hari Mohan Dubey (editor),Jagdish Chand Bansal (editor)
Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale
Lakshmanan, Valliappa;Tigani, Jordan
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
Applied Natural Language Processing with Python: Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing
Taweh Beysolow II
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
Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (4 volumes)
Cheng Few Lee (editor), John C. Lee (editor)
Automated Machine Learning with Microsoft Azure: Build highly accurate and scalable end-to-end AI solutions with Azure AutoML
Dennis Michael Sawyers
Principles of Data Mining
David J. Hand,Heikki Mannila,Padhraic Smyth
MACHINE LEARNING WITH PYTORCH AND SCIKIT-LEARN : develop machine learning and deep learning... models with scikit-learn and pytorch.
SEBASTIAN LIU YUXI (HAYDEN) MIRJALILI VAHID RASCHKA
Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
Jeff Heaton
Machine Learning with Health Care Perspective (Learning and Analytics in Intelligent Systems, 13)
Jain
Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter: Build scalable real-world projects to implement end-to-end neural networks on Android and iOS
Anubhav Singh,Rimjhim Bhadani
Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (in 4 Volumes)
Cheng F. Lee;John C Lee
State-of-the-Art Deep Learning Models in TensorFlow: Modern Machine Learning in the Google Colab Ecosystem
David Paper (auth.)
Journal of Machine Learning Research
Frezza-Buet, Hervé (author);Geist, Matthieu (author)
Python Natural Language Processing: Advanced machine learning and deep learning techniques for natural language processing
Jalaj Thanaki
Fundamentals of Machine Learning for Predictive Data Analytics : Algorithms, Worked Examples, and Case Studies
John D. Kelleher; Brian Mac Namee; Aoife D’Arcy
Evolutionary Computation for Modeling and Optimization
Daniel Ashlock
Artificial Superintelligence: A Futuristic Approach
Roman V. Yampolskiy
Graph-Powered Analytics and Machine Learning with TigerGraph: Driving Business Outcomes with Connected Data
Victor Lee,Phuc Kien Nguyen,Alexander Thomas
Mastering Computer Vision with PyTorch and Machine Learning 2024
Xiao C.
Mathematics of Machine Learning: Lecture Notes
Prof. Philippe Rigollet
Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data
Zeljko Ivezic,Andrew J. Connolly,Jacob T VanderPlas,Alexander Gray
Gaussian Processes for Machine Learning
Carl Edward Rasmussen,Christopher K. I. Williams