AIToolbox VS Caffe2

Compare AIToolbox vs Caffe2 and see what are their differences.


A toolbox of AI modules written in Swift: Graphs/Trees, Support Vector Machines, Neural Networks, PCA, K-Means, Genetic Algorithms (by KevinCoble)


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AIToolbox Caffe2
0 0
774 8,443
- -
0.0 0.0
over 2 years ago over 4 years ago
Swift Jupyter Notebook
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.


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

We haven't tracked posts mentioning AIToolbox yet.
Tracking mentions began in Dec 2020.


Posts with mentions or reviews of Caffe2. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Caffe2 yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing AIToolbox and Caffe2 you can also consider the following projects:

Caffe - Caffe: a fast open framework for deep learning.

mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!

Porcupine   - On-device wake word detection powered by deep learning

CoreML-Models - Largest list of models for Core ML (for iOS 11+)

Swift-AI - The Swift machine learning library.

Theano - Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as aesara:

Swift-Brain - Artificial intelligence/machine learning data structures and Swift algorithms for future iOS development. bayes theorem, neural networks, and more AI.

xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple