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- Machine learning on big data: Opportunities and challenges
- 100+ Free Data Science Books
- Deep learning applications and challenges in big data analytics
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Machine learning on big data: Opportunities and challenges
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100+ Free Data Science Books
Metrics details. Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can contain useful information about problems such as national intelligence, cyber security, fraud detection, marketing, and medical informatics. Companies such as Google and Microsoft are analyzing large volumes of data for business analysis and decisions, impacting existing and future technology. Deep Learning algorithms extract high-level, complex abstractions as data representations through a hierarchical learning process.
Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Big Data, Predictive Analytics and Machine Learning Abstract: Nowadays, data is being generated by so many devices, therefore the term big data. This paper attempts to offer a broader definition of big data that captures its defining characteristics.
Deep learning applications and challenges in big data analytics
Note that while every book here is provided for free, consider purchasing the hard copy if you find any particularly helpful. In many cases you will find Amazon links to the printed version, but bear in mind that these are affiliate links, and purchasing through them will help support not only the authors of these books, but also LearnDataSci. Thank you for reading, and thank you in advance for helping support this website. Comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.