What is Google AutoML Tables?
Enables your entire team of data scientists, analysts, and developers to automatically build and deploy machine learning models on structured data at massively increased speed and scale.
Google AutoML Tables is a tool in the Machine Learning Tools category of a tech stack.
Who uses Google AutoML Tables?
Companies
3 companies reportedly use Google AutoML Tables in their tech stacks, including Bayzat, Rhapsody, and AntEater Analytics.
Developers
19 developers on StackShare have stated that they use Google AutoML Tables.
Google AutoML Tables Integrations
Google AutoML Tables's Features
- Increases model quality
- Easy to build models
- Easy to deploy
- Flexible user options
- Doesn’t require a large annual licensing fee
Google AutoML Tables Alternatives & Comparisons
What are some alternatives to Google AutoML Tables?
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.
