Examples of using Machine-learning models in English and their translations into Chinese
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Such uncontrolled variables can be pernicious in machine-learning models.
Supervised machine-learning models boast remarkable predictive capabilities.
However, big data can help improve the accuracy of machine-learning models.
Black box machine-learning models are already having a major impact on some people's lives.
The higher-level Layers API is used to build machine-learning models on top of Core.
Spark MLib handles machine-learning models used for transforming datasets, which are represented as RDDs or DataFrames.
The higher-level Layers API is used to build machine-learning models on top of Core.
Machine-learning models, for instance, have been developed that can detect words and intonations of speech that may indicate depression.
All this compression work will only make existing machine-learning models 10 to 100 times smaller.
For instance, the company is taking advantage of Amazon SageMaker, a managed service for building, training,and deploying machine-learning models.
The former is secure, if limited by the size of machine-learning models used and device processor efficiency;
Neither option actually keeps the data frombeing used to train Alexa's myriad machine-learning models.
Companies like Google are coming up with slimmer machine-learning models, with the search giant targeting Android Wear 2.0 wearables.
Edge TPU is a purpose-built small-footprint ASICchip designed to run TensorFlow Lite machine-learning models on edge devices.
In this case,the study team evaluated how well eight machine-learning models were able to analyze patient data to predict which infants had sepsis.
Machine-learning models automatically adapt products to users' preferences, make recommendations for next steps and then suggest future features and products.
A large part of our research onsoftware systems continues to relate to building machine-learning models and to TensorFlow in particular.
But for newer, more cutting-edge machine-learning models, the CPU and its specialized machine-learning accelerators lend a helping hand.
Now, they have included a tool that instantly andautomatically generates machine-learning models to run prediction tasks on that data.
The UCSD team's goal is to create machine-learning models to correlate microbiome and clinical conditions, such as inflammation in autoimmune conditions.
The team is taking top-down andbottom-up approaches to the challenge of deploying machine-learning models onto resource-constrained devices.
Researchers have discovered that some machine-learning models have difficulty detecting adversarial input- that is, data constructed specifically to deceive the model. .
A large part of our research onsoftware systems continues to relate to building machine-learning models and to TensorFlow in particular.
Many other researchers have used machine-learning models to analyze data from biological experiments, by training an algorithm to generate predictions based on experimental data.
The long baseline of solar observations hasalso helped scientists form additional machine-learning models to try to predict when the Sun might release a CME.
Most AI giants on the internet rely on the continuous collection of personal data from their users,primarily to build and maintain machine-learning models.
This large accumulated data poolcan then be used to train machine-learning models for the implementation of preventive maintenance of the monitored equipment.
Traditionally, data scientists would need to spend weeks, or months,cleaning the data and designing machine-learning models to answer each question individually.
Then after measuring brain signals,scientists have developed personalized machine-learning models to recognize patterns of oxygenated hemoglobin levels related to pain responses.
Using the measured brain signals,the researchers developed personalized machine-learning models to detect patterns of oxygenated hemoglobin levels associated with pain responses.