Anonymous UserProject Manager & Database Administrator at a tech services company
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"All of the features of this product are quite good."
"The most valuable features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."
Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.
H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O’s supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models. The H2O platform is used by over 14,000 organizations globally and is extremely popular in both the R & Python communities.
Google Cloud Datalab is ranked 19th in Data Science Platforms with 1 review while H2O.ai is ranked 14th in Data Science Platforms with 1 review. Google Cloud Datalab is rated 8.0, while H2O.ai is rated 7.0. The top reviewer of Google Cloud Datalab writes "Stable, feature-rich, and easy to set up". On the other hand, the top reviewer of H2O.ai writes "Good collaboration functionality, but better integration with Python for data science is needed". Google Cloud Datalab is most compared with Databricks, IBM Watson Studio, Microsoft Azure Machine Learning Studio, Cloudera Data Science Workbench and MathWorks Matlab, whereas H2O.ai is most compared with KNIME, Dataiku Data Science Studio, Amazon SageMaker, Microsoft Azure Machine Learning Studio and Alteryx.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.