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Recommender System with Machine Learning and Artificial Intelligence
Author Sachi Nandan Mohanty , Jyotir Moy Chatterjee , Sarika
This book is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and ....
Release Date 2020/07 -
Real-World Natural Language Processing
Author Masato Hagiwara
Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you’ll create many interesting applications including a sentiment analyzer and a chatbot....
Release Date 2021/11 -
Author Henrik Brink Joseph W. Richards Mark Fetherolf
SummaryReal-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learning, preparing you....
Release Date 2016/09 -
Raspberry Pi Computer Vision Programming
Author Ashwin Pajankar
Design and implement your own computer vision applications with the Raspberry PiIn DetailThis book will provide you with the skills you need to successfully design and implement your own Raspberry Pi and Python-based computer vision projects.From the beginning, this....
Release Date 2015/05 -
Author Olga Korotkova
Random Light Beams: Theory and Applications contemplates the potential in harnessing random light. This book discusses light matter interactions, and concentrates on the various phenomena associated with beam-like fields. It explores natural and man-made light field....
Release Date 2017/12 -
Author Paul Daugherty , H. James Wilson
Technology advances are making tech more . . . human. This changes everything you thought you knew about innovation and strategy.In their groundbreaking book, Human + Machine, Accenture technology leaders Paul R. Daugherty and H. James Wilson showed how leading organizations use the power of human-m....
Release Date 2022/04 -
R: Unleash Machine Learning Techniques
Author Cory Lesmeister , Brett Lantz , Dipanjan Sarkar , Raghav Bali
Find out how to build smarter machine learning systems with R. Follow this three module course to become a more fluent machine learning practitioner.About This BookBuild your confidence with R and find out how to solve a huge range of data-related problemsGet to gr....
Release Date 2016/10 -
Author Dipanjan Sarkar , Raghav Bali
Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfullyAbout This BookGet to grips with the concepts of machine learning through exciting real-world examplesVisualize and so....
Release Date 2016/03 -
Author Pablo Maldonado , Yuxi Liu
5 real-world projects to help you master deep learning conceptsAbout This BookMaster the different deep learning paradigms and build real-world projects related to text generation, sentiment analysis, fraud detection, and moreGet to grips with R's impressive range....
Release Date 2018/02 -
Author Dr. Joshua F. Wiley
Build automatic classification and prediction models using unsupervised learningAbout This BookHarness the ability to build algorithms for unsupervised data using deep learning concepts with RMaster the common problems faced such as overfitting of data, anomalous d....
Release Date 2016/03 -
Author Joshua F. Wiley , Mark Hodnett
Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNetKey FeaturesUse R 3.5 for building deep learning models for computer vision and text Apply deep learning techniques in cloud for large-scale processing Build, train, and optimize neural netw....
Release Date 2018/08 -
Author Achyutuni Sri Krishna Rao , Dr. PKS Prakash
Powerful, independent recipes to build deep learning models in different application areas using R librariesAbout This BookMaster intricacies of R deep learning packages such as mxnet & tensorflowLearn application on deep learning in different domains using pra....
Release Date 2017/08 -
Quantum Machine Learning and Optimisation in Finance
Author Antoine Jacquier , Oleksiy Kondratyev , Alexander Lipton , Marcos López de Prado
Learn the principles of quantum machine learning and how to apply themWhile focus is on financial use cases, all the methods and techniques are transferable to other fieldsPurchase of Print or Kindle includes a free eBook in PDFKey FeaturesDiscover how to solve optimisation problems on quantum compu....
Release Date 2022/10 -
QOS-Enabled Networks, 2nd Edition
Author Peter Lundqvist , Miguel Barreiros
Written by two experts in the field who deal with QOS predicaments every day and now in this 2nd edition give special attention to the realm of Data Centers, QoS Enabled Networks:Tools and Foundations, 2nd Edition provides a lucid understanding of modern QOS theory....
Release Date 2016/02 -
PyTorch Recipes: A Problem-Solution Approach to Build, Train and Deploy Neural Network Models
Author Pradeepta Mishra
Learn how to use PyTorch to build neural network models using code snippets updated for this second edition. This book includes new chapters covering topics such as distributed PyTorch modeling, deploying PyTorch models in production, and developments around PyTorch with updated code.You'll start b....
Release Date 2022/12 -
Author Joe Papa
This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the t....
Release Date 2021/08 -
PyTorch Computer Vision Cookbook
Author Michael Avendi
Discover powerful ways to use deep learning algorithms and solve real-world computer vision problems using PythonKey FeaturesSolve the trickiest of problems in computer vision by combining the power of deep learning and neural networks Leverage PyTorch 1.x capabilities t....
Release Date 2020/03 -
PyTorch Artificial Intelligence Fundamentals
Author Jibin Mathew
Use PyTorch to build end-to-end artificial intelligence systems using PythonKey FeaturesBuild smart AI systems to handle real-world problems using PyTorch 1.x Become well-versed with concepts such as deep reinforcement learning (DRL) and genetic programming Cover PyTorc....
Release Date 2020/02 -
PyTorch 1.x Reinforcement Learning Cookbook
Author Yuxi Liu
Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipesKey FeaturesUse PyTorch 1.x to design and build self-learning artificial intelligence (AI) models Implement RL algorithms to solve control and optimization ch....
Release Date 2019/10 -
Python: Real World Machine Learning
Author Alberto Boschetti , Luca Massaron , Bastiaan Sjardin , John Hearty , Prateek Joshi
Learn to solve challenging data science problems by building powerful machine learning models using PythonAbout This BookUnderstand which algorithms to use in a given context with the help of this exciting recipe-based guideThis practical tutorial tackles real-world....
Release Date 2016/11 -
Python: Deeper Insights into Machine Learning
Author John Hearty , David Julian , Sebastian Raschka
Leverage benefits of machine learning techniques using Python.About This BookImprove and optimise machine learning systems using effective strategies.Develop a strategy to deal with a large amount of data.Use of Python code for implementing a range of machine learn....
Release Date 2016/08 -
Python Text Processing with NLTK 2.0 Cookbook
Author Jacob Perkins
Use Python's NLTK suite of libraries to maximize your Natural Language Processing capabilities.Quickly get to grips with Natural Language Processing - with Text Analysis, Text Mining, and beyondLearn how machines and crawlers interpret and process natural languages....
Release Date 2010/11 -
Python Natural Language Processing Cookbook
Get to grips with solving real-world NLP problems, such as dependency parsing, information extraction, topic modeling, and text data visualizationKey FeaturesAnalyze varying complexities of text using popular Python packages such as NLTK, spaCy, sklearn, and gensimImplement common and not-so-common .... -
Python Natural Language Processing
Author Jalaj Thanaki
Leverage the power of machine learning and deep learning to extract information from text dataAbout This BookImplement Machine Learning and Deep Learning techniques for efficient natural language processingGet started with NLTK and implement NLP in your application....
Release Date 2017/07 -
Python Machine Learning Workbook for Beginners
A practical guide to machine learning with Python through the presentation and guided completion of ten real-world projectsKey FeaturesStep-by-step roadmap to data science and machine learningA Python crash course in machine learning10 machine learning and data science projects for practical studyBo.... -
Python Machine Learning for Beginners
This course lays the foundations for both a theoretical and practical understanding of machine learning and artificial intelligence, utilizing Python as a beginner-friendly introduction and invitation to further studyKey FeaturesA crash course in Python programmingInteractive, guided practice throug.... -
Python Machine Learning Cookbook
Author Prateek Joshi
100 recipes that teach you how to perform various machine learning tasks in the real worldAbout This BookUnderstand which algorithms to use in a given context with the help of this exciting recipe-based guideLearn about perceptrons and see how they are used to buil....
Release Date 2016/06 -
Python Machine Learning By Example - Third Edition
Author Yuxi Liu
A comprehensive guide to get you up to speed with the latest developments of practical machine learning with Python and upgrade your understanding of machine learning (ML) algorithms and techniquesKey FeaturesDive into machine learning algorithms to solve the complex chal....
Release Date 2020/10 -
Python Machine Learning By Example - Second Edition
Author Yuxi Liu
Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learnKey FeaturesExploit the power of Python to explore the world of data mining and data analytics Discover machin....
Release Date 2019/02 -
Python Machine Learning Blueprints - Second Edition
Author Michael Roman , Alexander Combs
Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and KerasKey FeaturesGet to grips with Python's machine learning libraries including scikit-learn, Tens....
Release Date 2019/01