Uses of Package
deepnetts.data
Packages that use deepnetts.data
Package
Description
Support for automatically building deep learning models using hyper-parameter search.
Data structures to store example data used for building machine learning models.
Data normalization methods, used to scale data to specific range, in order to make them suitable for use by a neural network.
Evaluation procedures for machine learning models, used to estimate how good models are performing when given new data that (that was not used for training).
Neural network architectures with their corresponding builders.
Commonly used loss functions, which are used to calculate error during the training as a difference between predicted and target output.
Training algorithms and related utilities.
Various utility classes including Tensor, image operations, multithreading, exceptions etc.
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Classes in deepnetts.data used by deepnetts.automl
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Classes in deepnetts.data used by deepnetts.dataClassDescriptionExample image to train a deep learning model.Data set with images that will be used to train convolutional neural network.Single data item that will be used to train machine learning model.Basic data set with tabular data.This class holds training and test data set pair.
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Classes in deepnetts.data used by deepnetts.data.norm
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Classes in deepnetts.data used by deepnetts.eval
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Classes in deepnetts.data used by deepnetts.netClassDescriptionSingle data item that will be used to train machine learning model.Data pre-processing abstraction.
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Classes in deepnetts.data used by deepnetts.net.loss
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Classes in deepnetts.data used by deepnetts.net.train
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Classes in deepnetts.data used by deepnetts.utilClassDescriptionData set with images that will be used to train convolutional neural network.Data pre-processing abstraction.Basic data set with tabular data.Represents a basic data set item (single row) with input tensor and target vector in a data set.