GLOM-TensorFlow VS tf2-published-models

Compare GLOM-TensorFlow vs tf2-published-models and see what are their differences.

tf2-published-models

Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard. (by sarus-tech)
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GLOM-TensorFlow tf2-published-models
4 1
36 38
- -
0.0 0.0
about 3 years ago over 2 years ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

GLOM-TensorFlow

Posts with mentions or reviews of GLOM-TensorFlow. We have used some of these posts to build our list of alternatives and similar projects.

tf2-published-models

Posts with mentions or reviews of tf2-published-models. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-17.

What are some alternatives?

When comparing GLOM-TensorFlow and tf2-published-models you can also consider the following projects:

InvoiceNet - Deep neural network to extract intelligent information from invoice documents.

differential-privacy - Google's differential privacy libraries.

image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

dp-xgboost

efficientnet-lite-keras - Keras reimplementation of EfficientNet Lite.

privacy - Library for training machine learning models with privacy for training data

image-quality-assessment - Convolutional Neural Networks to predict the aesthetic and technical quality of images.

wtte-rnn - WTTE-RNN a framework for churn and time to event prediction

cnn-raccoon - Create interactive dashboards for your Convolutional Neural Networks with a single line of code!

head-pose-estimation - Realtime human head pose estimation with ONNXRuntime and OpenCV.

ydata-synthetic - Synthetic data generators for tabular and time-series data

Speech_driven_gesture_generation_with_autoencoder - This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".