Fast-Transformer VS embedding-encoder

Compare Fast-Transformer vs embedding-encoder and see what are their differences.

Fast-Transformer

An implementation of Fastformer: Additive Attention Can Be All You Need, a Transformer Variant in TensorFlow (by Rishit-dagli)
Machine Learning Transformers attention-mechanism Deep Learning Artificial intelligence Tensorflow Keras
Source Code
Suggest alternative
Edit details

embedding-encoder

Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings. (by cpa-analytics)
Machine Learning Deep Learning scikit-learn Keras Tensorflow neural-networks categorical-features categorical-encoding Embeddings
Source Code
Suggest alternative
Edit details
InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured
Fast-Transformer embedding-encoder
4 1
146 40
- -
0.0 0.0
about 2 years ago 9 months ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 MIT License
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.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.

Fast-Transformer

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

embedding-encoder

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

What are some alternatives?

When comparing Fast-Transformer and embedding-encoder you can also consider the following projects:

reformer-pytorch - Reformer, the efficient Transformer, in Pytorch

machine_learning_complete - A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.

Perceiver - Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow

machine-learning-articles - 🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.

Conformer - An implementation of Conformer: Convolution-augmented Transformer for Speech Recognition, a Transformer Variant in TensorFlow/Keras

python-machine-learning-book-3rd-edition - The "Python Machine Learning (3rd edition)" book code repository

machine-learning-experiments - 🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Traffic-Lights-Classification-CNN - Coding and testing a convolutional neural network for classifying traffic lights, with Keras and Tensorflow, using LISA dataset.

TimeSformer-pytorch - Implementation of TimeSformer from Facebook AI, a pure attention-based solution for video classification

handson-ml - ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

Transformer-in-Transformer - An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches

machine-learning-book - Code Repository for Machine Learning with PyTorch and Scikit-Learn

Fast-Transformer vs reformer-pytorch embedding-encoder vs machine_learning_complete Fast-Transformer vs Perceiver embedding-encoder vs machine-learning-articles Fast-Transformer vs Conformer embedding-encoder vs python-machine-learning-book-3rd-edition Fast-Transformer vs machine-learning-experiments embedding-encoder vs Traffic-Lights-Classification-CNN Fast-Transformer vs TimeSformer-pytorch embedding-encoder vs handson-ml Fast-Transformer vs Transformer-in-Transformer embedding-encoder vs machine-learning-book