Use data analytics to drive innovation and value throughout your network infrastructure Network and IT professionals capture immense amounts of data from their networks.
Data Analytics using Machine Learning Techniques on Cloud Platforms examines how machine learning (ML) and cloud computing combine to drive data-driven decision-making across industries.
Mikhail Zhilkin, a data scientist who has worked on projects ranging from Candy Crush games to Premier League football players' physical performance, shares his strong views on some of the best and, more importantly, worst practices in data analytics and business intelligence.
Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and KubernetesKey FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book DescriptionThe increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models.
The book discusses the activities involved in developing an Enterprise Continuity Program (ECP) that will cover both Business Continuity Management (BCM) as well as Disaster Recovery Management (DRM).
You can measure practically anything in the age of social media, but if you dont know what youre looking for, collecting mountains of data wont yield a grain of insight.
The application of internet of things (IoT) technologies and artificial intelligence (AI)-enabled IoT solutions has gradually become accepted by business and production organizations as an effective tool for automating several activities effectively and efficiently and developing and distributing products to the global market.
"e;Ulf Mattsson leverages his decades of experience as a CTO and security expert to show how companies can achieve data compliance without sacrificing operability.
Learn all the foundational Python you'll need to solve real data science problems Data science and machine learning--two of the world's hottest fields--are attracting talent from a wide variety of technical, business, and liberal arts disciplines.
This book offers an introduction and hands-on examples that demonstrate how Learning Analytics (LA) can be used to enhance digital learning, teaching and training at various levels.
Information Security Analytics gives you insights into the practice of analytics and, more importantly, how you can utilize analytic techniques to identify trends and outliers that may not be possible to identify using traditional security analysis techniques.
The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options.
This book constitutes the selected papers from the scientific satellite events held in conjunction with the19th International Conference on Service-Oriented Computing, ICSOC 2021.
Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis.
Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems.
This book constitutes the thoroughly refereed post-workshop proceedings of the 20th Chinese Lexical Semantics Workshop, CLSW 2019, held in Chiayi, Taiwan, in June 2019.
In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark.
Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework.
The three volume proceedings LNAI 10534 - 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017.
The three-volume set of LNCS 11921,11922, and 11923 constitutes the refereed proceedings of the 25th International Conference on the Theory and Applications of Cryptology and Information Security, ASIACRYPT 2019, held in Kobe, Japan, in December 2019.
Due to the increasing complexity in application workloads and query engines, database administrators are turning to automated tuning tools that systematically explore the space of physical design alternatives.
This book focusses on the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care.
This updated book describes optimization models of clustering problems and clustering algorithms based on optimization techniques, including their implementation, evaluation, and applications.
Intelligent and sustainable manufacturing is a broad category of manufacturing that employs computer-integrated manufacturing, high levels of adaptability and rapid design changes, digital information technology, and more flexible technical workforce training.
The two-volume set LNAI 10191 and 10192 constitutes the refereed proceedings of the 9th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2017, held in Kanazawa, Japan, in April 2017.
This edited volume examines the transformative impact of AI technologies on global healthcare systems, with a focus on enhancing efficiency and accessibility.
Accelerate your journey to smarter decision making by mastering the fundamentals of data literacy and developing the mindset to work confidently with dataKey FeaturesGet a solid grasp of data literacy fundamentals to support your next steps in your careerLearn how to work with data and extract meaningful insights to take the right actionsApply your knowledge to real-world business intelligence projectsBook DescriptionData is more than a mere commodity in our digital world.
Revamp your data landscape and implement highly effective data pipelines in AWS with this hands-on guidePurchase of the print or Kindle book includes a free PDF eBookKey FeaturesExecute extract, transform, and load (ETL) tasks on data lakes, data warehouses, and databasesImplement effective Pandas data operation with data wranglerIntegrate pipelines with AWS data servicesBook DescriptionData wrangling is the process of cleaning, transforming, and organizing raw, messy, or unstructured data into a structured format.