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  4. Machine Learning As A Service
  5. Cloud AI Platform Pipelines vs Sportlingo

Cloud AI Platform Pipelines vs Sportlingo

OverviewComparisonAlternatives

Overview

Cloud AI Platform Pipelines
Cloud AI Platform Pipelines
Stacks0
Followers6
Votes0
Sportlingo
Sportlingo
Stacks0
Followers1
Votes1

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Detailed Comparison

Cloud AI Platform Pipelines
Cloud AI Platform Pipelines
Sportlingo
Sportlingo

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.

AI-powered sports analytics and skill assessment API that enables apps and platforms to deliver personalized training, drills, and performance insights.

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
AI, Machine Learning, Analytics, API, Sports Analytics, Developer Tools
Statistics
Stacks
0
Stacks
0
Followers
6
Followers
1
Votes
0
Votes
1
Integrations
Google BigQuery
Google BigQuery
Google Cloud Functions
Google Cloud Functions
Google Cloud Dataflow
Google Cloud Dataflow
Google Kubernetes Engine
Google Kubernetes Engine
Google AI Platform
Google AI Platform
No integrations available

What are some alternatives to Cloud AI Platform Pipelines, Sportlingo?

Keen

Keen

Keen is a powerful set of API's that allow you to stream, store, query, and visualize event-based data. Customer-facing metrics bring SaaS products to the next level with acquiring, engaging, and retaining customers.

Snowplow

Snowplow

Snowplow is a real-time event data pipeline that lets you track, contextualize, validate and model your customers’ behaviour across your entire digital estate.

NanoNets

NanoNets

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

Inferrd

Inferrd

It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

Quickmetrics

Quickmetrics

It is a service for collecting, analyzing and visualizing custom metrics. It can be used to track anything from signups to server response times. Sending events is super simple.

Ahoy

Ahoy

Ahoy provides a solid foundation to track visits and events in Ruby, JavaScript, and native apps.

GraphLab Create

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.

digna

digna

Is the game-changing European modern data quality platform that effortlessly uncovers anomalies and errors in your data with Artificial Intelligence.

Bitdeli

Bitdeli

Build dashboards and reports with exactly the metrics you need using plain Python scripts. There is nothing new to learn. Bitdeli keeps your results up to date, no matter how much data you have or how complex your metrics are. Get started in minutes with our growing library of open-source analytics, created by experienced data hackers.

BigML

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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