ngram
Ngram-based models for compressing and classifying text (by TomLippincott)
tensorflow
Haskell bindings for TensorFlow (by tensorflow)
| ngram | tensorflow | |
|---|---|---|
| - | 2 | |
| 3 | 1,567 | |
| - | 0.4% | |
| 0.0 | 2.4 | |
| almost 4 years ago | 9 months ago | |
| Haskell | Haskell | |
| BSD 3-clause "New" or "Revised" License | 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.
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.
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.
ngram
Posts with mentions or reviews of ngram.
We have used some of these posts to build our list of alternatives
and similar projects.
We haven't tracked posts mentioning ngram yet.
Tracking mentions began in Dec 2020.
tensorflow
Posts with mentions or reviews of tensorflow.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-27.
-
Is Haskell okay for prototyping machine learning models for research (discovery and exploration)
If you require JAX, you'll be out of luck using Haskell. But there is Hasktorch, http://hasktorch.org/, and Tensorflow bindings in Haskell, https://github.com/tensorflow/haskell. Both seem to be actively maintained.
-
Haskell deep learning tutorials [Blog]
First I still have to admit that Haskell ML libraries have a large space for improvement. On the other hand, there exists bindings for Tensorflow. As can be seen from Github, they have recently added support for libtensorflow v2.3.0.
What are some alternatives?
When comparing ngram and tensorflow you can also consider the following projects:
HLearn-algebra - Homomorphic machine learning
haskell-ml - Various examples of machine learning, in Haskell.
rc - Reservoir Computing, an RNN flavor
grenade - Deep Learning in Haskell
genetics - A Genetic Algorithm library in Haskell
neural - Neural Nets in native Haskell
htvm - Haskell experiments involving TVM AI framework
hasktorch - Tensors and neural networks in Haskell