Sentence examples for machine learning training from inspiring English sources
"machine learning training" is grammatically correct and can be used in written English
It refers to the process of teaching a machine or computer system to learn and improve its performance through data and algorithms. Example: "Our company offers comprehensive machine learning training to equip employees with the skills to develop and implement advanced AI solutions."
The challenges in the red cluster were likely reasonably dissimilar to the other substances in the machine learning training sets, as the combinatorial fragmenters outperformed the CSI approaches clearly in this cluster.
The UAE team behind this new machine learning training model for lip reading have been looking purely at visual inputs — so training their model on the shape of the mouth as certain sounds are spoken, without any audio input cues at all.
It's also building graph-framework software for interfacing with the hardware, called Poplar, designed to mesh with different machine learning frameworks to enable developers to easily tap into a system that it claims will increase the performance of both machine learning training and inference by 10x to 100x vs the "fastest systems today".
Other use cases include connected feature extraction, a common machine learning training techniques that can look at a lot of data and extract the connections, the context and the relationships for a particular piece of data, such as suspects in a criminal case and the people connected to them.
Incomplete and duplicate sequences were removed to minimize bias in the machine learning training process.
These labs offer a wide range of machine learning-centric training options, collaborative workspaces for teams that are part of the company's four-week machine learning training program, and access to Google experts.
And, of course, Yelp is jumping on the machine learning train.
Here we develop tools to improve the analysis of genetic redundancy by (1) creating a database of comparative information on gene pairs based on sequence and expression characteristics, and, (2) predicting genetic redundancy genome wide using machine learning trained with known cases of genetic redundancy.
Of course, because of natural language processing constraints and machine learning model training time, this full vision is at least a couple of years out, according to Messina.
The dataset is derived from photos on Flickr and is used in machine learning for training and testing purposes.
In order to apply machine learning methods, training and test data were cross-normalised using an empirical Bayes approach of the Bioconductor package virtualArray[ 48] or a rank normalisation method of the package demi[ 49].
