Intersection Machine Learning Computational (7 results)
- Hardcover
Seller: Majestic Books, Hounslow, , United KingdomMajestic Books
Contact seller4-star sellerCondition: New
£ 197.60
£ 6.50 shippingShips from United Kingdom to U.S.A.Quantity: 3 available
Condition: New.
- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
Contact seller4-star sellerCondition: New
£ 222.79
£ 2.97 shippingShips within U.S.A.Quantity: 3 available
Condition: New.
- Hardcover
Seller: moluna, Greven, , Germanymoluna
Contact seller5-star sellerCondition: New
£ 187.47
£ 42.27 shippingShips from Germany to U.S.A.Quantity: Over 20 available
Condition: New.
- Hardcover
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
Contact seller4-star sellerCondition: New
£ 227.26
£ 8.59 shippingShips from Germany to U.S.A.Quantity: 3 available
Condition: New.
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
£ 231.26
£ 55.40 shippingShips from Germany to U.S.A.Quantity: 2 available
Buch. Condition: Neu. Neuware - The text employs computational techniques and large-scale data analysis to study complex social phenomena and human behavior. It discusses diverse methodologies, including agent-based modeling, network analysis, natural language processing, and machine learning, to gain insights into topics rangin…g from social network dynamics and opinion formation to economic trends and public health crises.Features: - Discusses the theoretical background of each algorithm in detail and presents the applications of each method. - Presents artificial intelligence implications, sustainable artificial intelligence, and the importance of artificial intelligence in agriculture, and energy. - Explains the use of predictive modeling in computational social science and applications of computational social science. - Showcases the framework for social network analysis, application program interface, data collection methods, and data preprocessing. - Covers topics such as density-based spatial clustering of applications with noise, the role of clustering in computational social science, and clustering in network structure. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
- Hardcover
- Print on Demand
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contact seller5-star sellerCondition: New
£ 204.25
Free ShippingShips within U.S.A.Quantity: 1 available
Hardcover. Condition: new. Hardcover. The text employs computational techniques and large-scale data analysis to study complex social phenomena and human behavior. It discusses diverse methodologies, including agent-based modeling, network analysis, natural language processing, and machine learning, to gain insights into topics…ranging from social network dynamics and opinion formation to economic trends and public health crises.Features:Discusses the theoretical background of each algorithm in detail and presents the applications of each method.Presents artificial intelligence implications, sustainable artificial intelligence, and the importance of artificial intelligence in agriculture, and energy.Explains the use of predictive modeling in computational social science and applications of computational social science.Showcases the framework for social network analysis, application program interface, data collection methods, and data preprocessing.Covers topics such as density-based spatial clustering of applications with noise, the role of clustering in computational social science, and clustering in network structure.The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text discusses theoretical background of algorithms and applications of methods using social science problems. It explores different machine-learning approaches to tackle the current issues in the digital world by analyzing social networks. It discusses topics such as principles of semi-supervised learning, and reinforcement algorithms. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Hardcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
Contact seller5-star sellerCondition: New
£ 219.49
£ 37.00 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Hardcover. Condition: new. Hardcover. The text employs computational techniques and large-scale data analysis to study complex social phenomena and human behavior. It discusses diverse methodologies, including agent-based modeling, network analysis, natural language processing, and machine learning, to gain insights into topics…ranging from social network dynamics and opinion formation to economic trends and public health crises.Discusses the theoretical background of each algorithm in detail and presents the applications of each method.Presents artificial intelligence implications, sustainable artificial intelligence, and the importance of artificial intelligence in agriculture, and energy.Explains the use of predictive modeling in computational social science and applications of computational social science.Showcases the framework for social network analysis, application program interface, data collection methods, and data preprocessing.Covers topics such as density-based spatial clustering of applications with noise, the role of clustering in computational social science, and clustering in network structure.The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text discusses theoretical background of algorithms and applications of methods using social science problems. It explores different machine-learning approaches to tackle the current issues in the digital world by analyzing social networks. It discusses topics such as principles of semi-supervised learning, and reinforcement algorithms. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
