Cloud AI Platform Pipelines vs Kaggle
Overview
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It provides a way to deploy robust, repeatable machine learning pipelines along with monitoring, auditing, version tracking, and reproducibility, and delivers an enterprise-ready, easy to install, secure execution environment for your ML workflows. | Machine learners share, stress test, and stay up-to-date on all the latest ML techniques and technologies. Discover a huge repository of community-published models, data & code for your next project. |
Push-button installation via the Google Cloud Console; Enterprise features for running ML workloads, including pipeline versioning, automatic metadata tracking of artifacts and executions, Cloud Logging, visualization tools, and more; Seamless integration with Google Cloud managed services like BigQuery, Dataflow, AI Platform Training and Serving, Cloud Functions, and many others ; Many prebuilt pipeline components (pipeline steps) for ML workflows, with easy construction of your own custom components | Find all the resources and knowledge needed for your next real-world ML project;
High-quality public datasets. Everything from avocado prices to video game sales;
Public notebooks and access to a powerful notebook environment with no cost GPUs & TPUs;
Pre-trained, ready-to-deploy ML models;
Build your ML skills in a supportive and helpful community |
Statistics | |
Stacks 0 | Stacks 10 |
Followers 6 | Followers 7 |
Votes 0 | Votes 0 |
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What are some alternatives to Cloud AI Platform Pipelines, Kaggle?
Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
NanoNets
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NumPy
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
Inferrd
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PyXLL
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GraphLab Create
Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.
BigML
BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.
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