Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Armando Fandango"'
Understand data analysis pipelines using machine learning algorithms and techniques with this practical guideKey FeaturesPrepare and clean your data to use it for exploratory analysis, data manipulation, and data wranglingDiscover supervised, unsuper
Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projectsKey FeaturesUse machine learning and deep learning principles to build real-world projectsGet to grips
Autor:
Armando Fandango
Build, scale, and deploy deep neural network models using the star libraries in Python Key FeaturesDelve into advanced machine learning and deep learning use cases using Tensorflow and KerasBuild, deploy, and scale end-to-end deep neural network mode
Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problemsKey FeaturesMaster supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for
Autor:
Armando Fandango, Ivan Idris
Learn how to apply powerful data analysis techniques with popular open source Python modulesKey Features[•]Find, manipulate, and analyze your data using the Python 3.5 libraries[•]Perform advanced, high-performance linear algebra and mathematical
Publikováno v:
Artificial Intelligence and Machine Learning in Defense Applications IV.
学习Python编程,轻松应对大数据分析任务,掌握信号处理、时间序列、文本数据分析、机器学习等高级技能Key Features在本书的最后,采用3个附录的形式为读者补充了一些重要概念、常用函数
Autor:
Armando Fandango, R. Paul Wiegand
Publikováno v:
ICISDM
The smart cities of modern nations rely on the smooth flow of transportation that depends on the predictions of the traffic flow patterns. Since last few years, deep learning based methods have emerged to show better results for short-term traffic ow
Autor:
Amita Kapoor, Armando Fandango
Publikováno v:
Communications in Computer and Information Science ISBN: 9789811318122
For more than 40 years, various statistical time series forecasting, and machine learning methods have been applied to predict the short-term traffic flow. More recently, deep learning methods have emerged to show better results for short-term traffi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7427c215a4f6dcb36e162e4823351ca6
https://doi.org/10.1007/978-981-13-1813-9_43
https://doi.org/10.1007/978-981-13-1813-9_43
Autor:
Armando Fandango, William A. Rivera
Scientific Big Data being gathered at exascale needs to be stored, retrieved and manipulated. The storage stack for scientific Big Data includes a file system at the system level for physical organization of the data, and a file format and input/outp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4f0658a53c2dd4b2c69b8e903cad795
https://doi.org/10.4018/978-1-5225-3142-5.ch010
https://doi.org/10.4018/978-1-5225-3142-5.ch010