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“…Annotation Applications and experiments in all areas of science are becoming increasingly complex and more demanding in terms of their computational and data requirements Some applications generate data volumes reaching hundreds of terabytes and even petabytes Analyzing, visualizing, and disseminating these large data sets has become a major challenge and data intensive computing is now considered as the fourth paradigm in scientific discovery after theoretical, experimental, and computational science As scientific applications become more data intensive, the technologies of handling Big Data have gathered great importance This necessity has made that applications have seen an increasing adoption on clouds infrastructures The computing models, system software, programming models, analysis frameworks, and other clouds services need to evolve and accommodate them to face the challenge of big data applications…”

“…They define what must be governed, identify key stakeholders, and review the relationship of SOA governance to existing governance bodies as well as governance frameworks like COBIT. Next, they walk you through SOA governance assessment and planning, identifying and fixing gaps, setting goals and objectives, and establishing workable roadmaps and governance deliverables. …”

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“…For her, participating in the immediate cultural debates in Estonia and Finland was a priority, yet her whole oeuvre is a negotiation between her more immediate contexts and the leading conceptual frameworks of aesthetics, geniality, knowledge, subjectivity, race, sexuality, nature, etc., circling in Europe at the end of the 19th and the beginning of the 20th century. …”

“…Covering major topics such as big tech, data analytics, artificial intelligence, blockchain, cryptocurrency, autonomy, cybersecurity, data privacy, and antitrust, strategy expert Michael Lenox outlines a set of novel, original frameworks to help those undertaking digital transformation at their organization devise their strategy. …”

“…Moving ahead, you'll explore the mathematical frameworks crucial for machine learning algorithms. …”

“…Learn about various instructional design models and frameworks, then discover the different options for designing learning experiences. …”

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“…Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the discipline without actually understanding data science. …”

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“…Learn Python programming and Scikit-Learn applied to machine learning regression in this comprehensive guide for beginners About This Video Learn how to use different frameworks in Python to solve real-world problems using deep learning and artificial intelligence Build artificial neural networks with TensorFlow and Keras Make predictions using linear regression, polynomial regression, and multivariate regression In Detail Machine learning is a branch of computer science in which you can use mathematical input to develop complicated models that fulfil various roles. …”

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