machine learning [ muh-sheen lur-ning ] Phonetic (Standard) IPA noun Computers, Digital Technology. the capacity of a computer to process and evaluate data beyond programmed algorithms, through contextualized inference (often used attributively). cognitive computing ( def ), deep learning ( def )...
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A curated list of awesome Machine Learning frameworks, libraries and software. - josephmisiti/awesome-machine-learning
The meaning of MACHINE is a mechanically, electrically, or electronically operated device for performing a task. How to use machine in a sentence.
Machine learning has many applications—and the possibilities are constantly expanding. Here are some of the top benefits that businesses have achieved with their machine learning projects: Uncover insight Machine learning can help identify a pattern or structure within both structured and unstructured...
Once a DataFrame is loaded, defined a "ProblemDefinition" via a dictionary. The only thing a user needs to specify is the name of the column to predict (via the key target). Create a JSON-AI syntax from the command json_ai_from_problem. Lightwood can then use this object to ...
Awesome Machine Learning A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php.If you want to contribute to this list (please do), send me a pull request or contact me @josephmisiti. Also, a listed repository should be deprecated...
介绍:Francis Bach合作的有关稀疏建模的新综述(书):Sparse Modeling for Image and Vision Processing,内容涉及Sparsity, Dictionary Learning, PCA, Matrix Factorization等理论,以及在图像和视觉上的应用,而且第一部分关于Why does the l1-norm induce sparsity的解释也很不错。 《Reproducing Kernel Hilbert Space》 ...
Bill Wilson. The machine learning dictionary. www.cse.unsw.edu.au/ ~billw/mldict.html, 25 June 2012. Accessed: February 25, 2016.B. Wilson, "The Machine Learning Dictionary". 2012B. Wilson, "The Machine Learning Dictionary," 1998 - 2012. [Online]. Available: http://www.cse.unsw.edu...
《Deep Learning in Neural Networks: An Overview》 介绍:这是瑞士人工智能实验室Jurgen Schmidhuber写的最新版本《神经网络与深度学习综述》本综述的特点是以时间排序,从1940年开始讲起,到60-80年代,80-90年代,一直讲到2000年后及最近几年的进展。涵盖了deep learning里各种tricks,引用非常全面....