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Big data opportunities

Xem 1-9 trên 9 kết quả Big data opportunities
  • This era of groundbreaking scientific developments in high-resolution, high-throughput technologies is allowing the cost-effective collection and analysis of huge, disparate datasets on individual health. Proper data mining and translation of the vast datasets into clinically actionable knowledge will require the application of clinical bioinformatics.

    pdf11p vioraclene 31-03-2024 1 1   Download

  • Ebook Big data bootcamp: Part 2 presents the following content: Chapter 7: doing a big data project; chapter 8: the next billion-dollar IPO: Big data entrepreneurship; chapter 9: reach more customers with better data—and products; chapter 10: how big data is changing the way we live; chapter 11: big data opportunities in education; chapter 12: capstone case study: big data meets romance; Appendix A: Big data resources.

    pdf117p haojiubujain08 01-11-2023 3 2   Download

  • Ebook Big data in practice: How 45 successful companies used big data analytics to deliver extraordinary results - Part 1 presents the following content: Chapter 1 Walmart, Chapter 2 CERN, Chapter 3 Netflix, Chapter 4 Rolls-Royce, Chapter 5 Shell, Chapter 6 Apixio, Chapter 7 Lotus F1 Team, Chapter 8 Pendleton & Son Butchers, Chapter 9 US Olympic Womens Cycling Team, Chapter 10 ZSL, Chapter 11 Facebook, Chapter 12 John Deere, Chapter 13 Royal Bank of Scotland, Chapter 14 LinkedIn, Chapter 15 Microsoft, Chapter 16 Acxiom, Chapter 17 US Immigration And Customs, Chapter 18 Nest, Chapter 19 GE, ...

    pdf182p haojiubujain01 06-06-2023 25 4   Download

  • Ebook Big data in practice: How 45 successful companies used big data analytics to deliver extraordinary results - Part 2 presents the following content: Chapter 26 Sprint, Chapter 27 Dickeys Barbecue Pit, Chapter 28 Caesars, Chapter 29 Fitbit, Chapter 30 Ralph Lauren, Chapter 31 Zynga, Chapter 32 Autodesk, Chapter 33 Walt Disney Parks and Resorts, Chapter 34 Experian, Chapter 35 Transport for London, Chapter 36 The US Government, Chapter 37 IBM Watson, Chapter 38 Google, Chapter 39 Terra Seismic, Chapter 40 Apple, Chapter 41 Twitter, Chapter 42 Uber, Chapter 43 Electronic Arts, Chapter 44 ...

    pdf141p haojiubujain01 06-06-2023 6 5   Download

  • Clinical research data warehouses (RDWs) linked to genomic pipelines and open data archives are being created to support innovative, complex data-driven discoveries. The computing and storage needs of these research environments may quickly exceed the capacity of on-premises systems.

    pdf9p vighostrider 25-05-2023 5 2   Download

  • Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for querying, processing, and visualizing genomics’ “Big Data” from sources like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) without local software installation or configuration.

    pdf12p vikentucky2711 26-11-2020 11 0   Download

  • The focus of this research is to find solutions about millennial generation towards Big Data and other advanced technologies. The rise of the Industrial Revolution 4.0 produced large amounts of data so that they could provide various opportunities for the more developed industries.

    pdf14p orianahuynh 06-06-2020 12 2   Download

  • Due to the premature stage of big data research, the supply has not been able to keep up with the demand from organizations that want to leverage on big data analytics. Big data explorers and big data adopters struggle with access to qualitative as well as quantitative research on big data. The lack of access to big data know-how information, best practice advice and guidelines drove this study. The objective is to contribute to efforts being made to support a wider adoption of big data analytics.

    pdf99p nguyenyenyn117 14-06-2019 49 3   Download

  • The key primary aim is to provide state of the art knowledge about how deep learning evolved and revolutionized machine learning in the past few years. Second, to critically review the application of deep learning for different biomedical signals analysis and provide a holistic overview of current works of literature. Finally, to discuss the research opportunities with deep learning algorithms in the field of study that can serve as a starting point for new researchers to identify the future research direction in a concise manner.

    pdf15p guestgreat 16-05-2019 24 0   Download

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