Geo.Engineerings

Hisham El-Amir, Mahmoud Hamdy ... 551 pages - Publisher: Apress; (December, 2019) ... Language: English - ASIN: B082ZL1D59 by Amazon.

Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets. You'll also develop a deep learning project by preparing data, choosing the model that fits that data, and debugging your model to get the best fit to data all using Tensorflow techniques. Enhance your skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution or entering a Kaggle contest, Deep Learning Pipeline is for you!

What You'll Learn: Develop a deep learning project using data + Study and apply various models to your data + Debug and troubleshoot the proper model suited for your data.

Witold Pedrycz, Shyi-Ming Chen ... 360 pages - Publisher: Springer; (October, 2019) ... Language: English - ASIN: B07ZMY46RV by Amazon.

This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm’s algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.

Francesco Calvetti, Federica Cotecchia, Andrea Galli, Cristina Jommi ... 788 pages - Publisher: Springer; (June, 2019) - Language: English - AmazonSIN: B07T8QWXJ8.

This volume gathers the latest advances, innovations, and applications in the field of geotechnical engineering, as presented by leading researchers and engineers at the 7th Italian National Congress of Geotechnical Researchers (CNRIG 2019), entitled “Geotechnical Research for the Protection and Development of the Territory” (Lecco, Italy, July 3-5, 2019). The congress is intended to promote exchanges on the role of geotechnical research and its findings regarding the protection against natural hazards, design criteria for structures and infrastructures, and the definition of sustainable development strategies. The contributions cover a diverse range of topics, including infrastructural challenges, underground space utilization, and sustainable construction in problematic soils and situations, as well as geo-environmental aspects such as landfills, environmental and energy geotechnics, geotechnical monitoring, and risk assessment and mitigation. Selected by means of a rigorous peer-review process, they will spur novel research directions and foster future multidisciplinary collaborations.