Kaggle vs Sportlingo
Overview
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Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.
CLI (Node.js)
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Detailed Comparison
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. | AI-powered sports analytics and skill assessment API that enables apps and platforms to deliver personalized training, drills, and performance insights. |
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 | AI, Machine Learning, Analytics, API, Sports Analytics, Developer Tools |
Statistics | |
Stacks 10 | Stacks 0 |
Followers 7 | Followers 1 |
Votes 0 | Votes 1 |
Integrations | |
| No integrations available | |
What are some alternatives to Kaggle, Sportlingo?
Keen
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Snowplow
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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
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.
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
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.
PyXLL
Integrate Python into Microsoft Excel. Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python. Works with all 3rd party and open source Python packages. No need to write any VBA!
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 provides a solid foundation to track visits and events in Ruby, JavaScript, and native apps.
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.
