• Exploring insider trading using hypernetworks
• Data-driven approach to detection of autism spectrum disorder
• Anonymization and sentiment analysis of Twitter posts
Theoretical papers in the book cover such topics as Optimal Regression Tree Models Through Mixed Integer Programming; Chance Influence in Datasets with Large Number of Features; Adversarial Networks — A Technology for Image Augmentation; and Optimal Regression Tree Models Through Mixed Integer Programming.
Five shorter student-track papers are also published here, on topics such as
• State-of-the-art Deep Learning Methods to effect Neural Machine Translation from Natural Language into SQL
• A Smart Recommendation System to Simplify Projecting for a HMI/SCADA Platform
• Use of Adversarial Networks as a Technology for Image Augmentation
• Using Supervised Learning to Predict the Reliability of a Welding Process
• Exploring insider trading using hypernetworks
• Data-driven approach to detection of autism spectrum disorder
• Anonymization and sentiment analysis of Twitter posts
Theoretical papers in the book cover such topics as Optimal Regression Tree Models Through Mixed Integer Programming; Chance Influence in Datasets with Large Number of Features; Adversarial Networks — A Technology for Image Augmentation; and Optimal Regression Tree Models Through Mixed Integer Programming.
Five shorter student-track papers are also published here, on topics such as
• State-of-the-art Deep Learning Methods to effect Neural Machine Translation from Natural Language into SQL
• A Smart Recommendation System to Simplify Projecting for a HMI/SCADA Platform
• Use of Adversarial Networks as a Technology for Image Augmentation
• Using Supervised Learning to Predict the Reliability of a Welding Process

Data Science - Analytics and Applications: Proceedings of the 2nd International Data Science Conference - iDSC2019
102
Data Science - Analytics and Applications: Proceedings of the 2nd International Data Science Conference - iDSC2019
102(2019)
Product Details
ISBN-13: | 9783658274948 |
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Publisher: | Springer Fachmedien Wiesbaden |
Publication date: | 10/10/2019 |
Edition description: | 2019 |
Pages: | 102 |
Product dimensions: | 8.27(w) x 10.98(h) x (d) |
Language: | German |