Dòng
|
Nội dung
|
1
|
|
2
|
Algorithms for next-generation sequencing / Wing-Kin Sung Boca Raton : CRC Press, 2017 347 pages. : illustrations ; 23 cm. Ký hiệu phân loại (DDC): 570.285 Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before - as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data? Algorithms for Next-Generation Sequencing is an invaluable tool for students and researchers in bioinformatics and computational biology, biologists seeking to process and manage the data generated by next-generation sequencing, and as a textbook or a self-study resource. In addition to offering an in-depth description of the algorithms for processing sequencing data, it also presents useful case studies describing the applications of this technology Số bản sách:
(1)
Tài liệu số:
(0)
|
3
|
Genetic algorithms and machine learning for programmers : create AI models and evolve solutions / Frances Buontempo [Raleigh, North Carolina] : The Pragmatic Bookshelf, 2019 234 pages. : illustrations ; cm. Ký hiệu phân loại (DDC): 005.1 Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you. Số bản sách:
(0)
Tài liệu số:
(1)
|
4
|
Genetic algorithms in search, optimization, and machine learning / David E. Goldberg Mass. : Addison-Wesley, Reading, 1989 xiii, 412 pages. : illustrations Ký hiệu phân loại (DDC): 006.31 This text introduces the theory, operation, and application of genetic algorithms- search algorithms based on the mechanics of natural selection and genetics. Although genetic algorithms are already considered to be an important methodology in the development of search and machine-learning methods, only recently have they received attention in other research and industrial circles Số bản sách:
(1)
Tài liệu số:
(0)
|
5
|
|
|
|
|
|