Modern data science with R. Benjamin S.Baumer, Daniel T.KaplanNicholas J.Horton(2021). CRC Press, Boca Raton. 631 pages, ISBN: 9780367191498

2021 ◽  
Author(s):  
Annika Hoyer
Keyword(s):  
Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery

Author(s):  
Shaveta Bhatia

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.


Author(s):  
Natalia V. Vysotskaya ◽  
T. V. Kyrbatskaya

The article is devoted to the consideration of the main directions of digital transformation of the transport industry in Russia. It is proposed in the process of digital transformation to integrate the community approach into the company's business model using blockchain technology and methods and results of data science; complement the new digital culture with a digital team and new communities that help management solve business problems; focus the attention of the company's management on its employees and develop those competencies in them that robots and artificial intelligence systems cannot implement: develop algorithmic, computable and non-linear thinking in all employees of the company.


2019 ◽  
Vol 5 (30) ◽  
pp. 960-968
Author(s):  
Güner Gözde KILIÇ
Keyword(s):  

2020 ◽  
Author(s):  
Saeed Nosratabadi ◽  
Amir Mosavi ◽  
Puhong Duan ◽  
Pedram Ghamisi ◽  
Ferdinand Filip ◽  
...  

This paper provides a state-of-the-art investigation of advances in data science in emerging economic applications. The analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which, based on the accuracy metric, outperform other learning algorithms. It is further expected that the trends will converge toward the advancements of sophisticated hybrid deep learning models.


2019 ◽  
Vol 114 (12) ◽  
pp. 874-877 ◽  
Author(s):  
Jürgen Mazarov ◽  
Patrick Wolf ◽  
Julian Schallow ◽  
Fabian Nöhring ◽  
Jochen Deuse ◽  
...  
Keyword(s):  

2019 ◽  
Vol 1 (2) ◽  
pp. 44-54
Author(s):  
Renato Marinho Alves ◽  
Alexandre Moraes Matos ◽  
Edna Dias Canedo
Keyword(s):  

O conceito de mineração e análise de dados se baseia na utilização de algoritmos computacionais e técnicas de exploração de conteúdo em um conjunto de dados de modo a se obter maiores informações sobre estes que possibilitem ao usuário ter um maior entendimento sobre os dados e a fonte das informações. Desta forma, foi criada área de ciência dos dados, do inglês \textit{data science}, que é atualmente empregada a utilização de técnicas científicas da computação visando a obtenção de informações implícitas em conjuntos de dados. Este trabalho apresenta a aplicação de técnicas de mineração e análise de dados seguindo o modelo CRISP-DM sobre os dados de respostas dos estudantes da área de Computação às provas do ENADE. Diante disso é apresentada uma plataforma para apresentação dos resultados obtidos da aplicação das técnicas.


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