Contents

tensorflow-model-analysis 0.46.0

0

A library for analyzing TensorFlow models

A library for analyzing TensorFlow models

Stars: 1256, Watchers: 1256, Forks: 277, Open Issues: 36

The tensorflow/model-analysis repo was created 6 years ago and the last code push was Yesterday.
The project is very popular with an impressive 1256 github stars!

How to Install tensorflow-model-analysis

You can install tensorflow-model-analysis using pip

pip install tensorflow-model-analysis

or add it to a project with poetry

poetry add tensorflow-model-analysis

Package Details

Author
Google LLC
License
Apache 2.0
Homepage
https://www.tensorflow.org/tfx/model_analysis/get_started
PyPi:
https://pypi.org/project/tensorflow-model-analysis/
GitHub Repo:
https://github.com/tensorflow/model-analysis

Classifiers

  • Scientific/Engineering
  • Scientific/Engineering/Artificial Intelligence
  • Scientific/Engineering/Mathematics
  • Software Development
  • Software Development/Libraries
  • Software Development/Libraries/Python Modules
No  tensorflow-model-analysis  pypi packages just yet.

Errors

A list of common tensorflow-model-analysis errors.

Code Examples

Here are some tensorflow-model-analysis code examples and snippets.

GitHub Issues

The tensorflow-model-analysis package has 36 open issues on GitHub

  • minor - typo correction
  • [Documentation] Correcting the link of the byte_value type info
  • Fix Typo

See more issues on GitHub

Related Packages & Articles

tensorflow 2.17.0

TensorFlow is an open source machine learning framework for everyone.

thinc 9.1.1

A refreshing functional take on deep learning, compatible with your favorite libraries

spacy 3.8.2

Industrial-strength Natural Language Processing (NLP) in Python

nlp 0.4.0

HuggingFace/NLP is an open library of NLP datasets.

keras 3.6.0

Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. The core data structures of Keras are layers and models. The philosophy is to keep simple things simple, while allowing the user to be fully in control when they need to (the ultimate control being the easy extensibility of the source code via subclassing).

gensim 4.3.3

Python framework for fast Vector Space Modelling