This book presents ample, richly illustrated account on results and experience from a project, dealing with the analysis of data concerning behavior patterns on the Web. The advertising on the Web is dealt with, and the ultimate issue is to assess the share of the artificial, automated activity (ads fraud), as opposed to the genuine human activity.After a comprehensive introductory part, a full-fledged report is provided from a wide range of analytic and design efforts, oriented at...

Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.Key Features\[\*\] Explore and create intelligent systems using cutting-edge deep learning techniques\[\*\] Implement deep learning algorithms and work with revolutionary libraries in Python\[\*\] Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and moreBook DescriptionWith an incr...

"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come."– Tim Urban, author of Wait But WhyFully Practical, Insightful Guide to Modern Deep LearningDeep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance....

This open access book describes the technologies needed to construct a secure big data infrastructure that connects data owners, analytical institutions, and user institutions in a circle of trust. It begins by discussing the most relevant technical issues involved in creating safe and privacy-preserving big data distribution platforms, and especially focuses on cryptographic primitives and privacy-preserving techniques, which are essential prerequisites. The book also covers elliptic curv...

Build next-generation Artificial Intelligence systems with JavaKey FeaturesImplement AI techniques to build smart applications using Deeplearning4jPerform big data analytics to derive quality insights using Spark MLlibCreate self-learning systems using neural networks, NLP, and reinforcement learningBook DescriptionIn this age of big data, companies have larger amount of consumer data than ever before, far more than what the ...

The book offers the readers the fundamental concepts of Machine Learning techniques in a user-friendly language. The book aims to give in-depth knowledge of the different Machine Learning (ML) algorithms and the practical implementation of the various ML approaches.This book covers different Supervised Machine Learning algorithms such as Linear Regression Model, Naïve Bayes classifier Decision Tree, K-nearest neighbor, Logistic Regression, Support Vector Machine, Random forest algorithms, ...

Build, implement and scale distributed deep learning models for large-scale datasets Key FeaturesGet to grips with the deep learning concepts and set up Hadoop to put them to useImplement and parallelize deep learning models on Hadoop’s YARN frameworkA comprehensive tutorial to distributed deep learning with HadoopBook DescriptionThis book will teach you how to deploy large-scale dataset in deep neural networks with Hadoop fo...

Machine Learning models are widely used in different fields such as Artificial Intelligence, Business, Clinical and Biological Sciences which includes self-driving cars, predictive models, disease prediction, genome sequencing, spam filtering, product recommendation, fraud detection and image recognition . It has gained importance due to its capabilities of handling large volume of data, prediction and classification accuracy and validation procedures.Machine Learning models are bu...

Your one-stop guide to learning and implementing artificial neural networks with Keras effectivelyKey FeaturesDesign and create neural network architectures on different domains using KerasIntegrate neural network models in your applications using this highly practical guideGet ready for the future of neural networks through transfer learning and predicting multi network modelsBook DescriptionNeural networks are used to solve...

This book constitutes the refereed proceedings of the 30th Australasian Joint Conference on Artificial Intelligence, AI 2017, held in Melbourne, VIC, Australia, in August 2017.The 29 full papers were carefully reviewed and selected from 58 submissions. This volume covers a wide spectrum of research streams in artificial intelligence ranging from machine learning, optimization to big data science and their practical applications.

Digital technologies transformed the people's day to day life and businesses organizations the way they work. It saved their time, accessibility and cost. It provided new opportunities, new markets, and new products to the organizations.Digital revolution started with the introduction of Computers, Internet, Mobile phones, Social media networks, Cloud computing, Big Data, Internet of Things, 3D Printing, Machine learning, Virtual reality, Natural Language Processing, Block Chain, A...

Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles.An Introduction to Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommen...