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TensorFlow: A system for large-scale machine learning

2 code implementations27 May 2016

TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments.

BIG-bench Machine Learning Management

TF.Learn: TensorFlow's High-level Module for Distributed Machine Learning

1 code implementation13 Dec 2016

TF. Learn is a high-level Python module for distributed machine learning inside TensorFlow.

BIG-bench Machine Learning

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

4 code implementations14 Mar 2016

TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms.

BIG-bench Machine Learning Dimensionality Reduction +3

TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning

1 code implementation27 Feb 2019

TensorFlow Eager is a multi-stage, Python-embedded domain-specific language for hardware-accelerated machine learning, suitable for both interactive research and production.

BIG-bench Machine Learning

TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks

1 code implementation8 Aug 2017

Our focus is on simplifying cutting edge machine learning for practitioners in order to bring such technologies into production.

BIG-bench Machine Learning

Adversarial Machine Learning at Scale

7 code implementations4 Nov 2016

Adversarial examples are malicious inputs designed to fool machine learning models.

BIG-bench Machine Learning

Scikit-learn: Machine Learning in Python

3 code implementations2 Jan 2012

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.

BIG-bench Machine Learning Dimensionality Reduction +2

A Machine Learning Data Fusion Model for Soil Moisture Retrieval

1 code implementation20 Jun 2022

We develop a deep learning based convolutional-regression model that estimates the volumetric soil moisture content in the top ~5 cm of soil.

BIG-bench Machine Learning Soil moisture estimation

Neural Additive Models: Interpretable Machine Learning with Neural Nets

6 code implementations NeurIPS 2021

They perform similarly to existing state-of-the-art generalized additive models in accuracy, but are more flexible because they are based on neural nets instead of boosted trees.

Additive models BIG-bench Machine Learning +2