What is Aerosolve?
This library is meant to be used with sparse, interpretable features such as those that commonly occur in search (search keywords, filters) or pricing (number of rooms, location, price). It is not as interpretable with problems with very dense non-human interpretable features such as raw pixels or audio samples.
Aerosolve is a tool in the Machine Learning Tools category of a tech stack.
Aerosolve is an open source tool with 4.8K GitHub stars and 567 GitHub forks. Here’s a link to Aerosolve's open source repository on GitHub
Who uses Aerosolve?
Companies
Developers
24 developers on StackShare have stated that they use Aerosolve.
Aerosolve's Features
- A thrift based feature representation that enables pairwise ranking loss and single context multiple item representation.
- A feature transform language gives the user a lot of control over the features
- Human friendly debuggable models
- Separate lightweight Java inference code
- Scala code for training
- Simple image content analysis code suitable for ordering or ranking images
Aerosolve Alternatives & Comparisons
What are some alternatives to Aerosolve?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
CUDA
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
