Kaggle vs Mineo
Overview
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Detailed Comparison
It is the platform to explore your data, develop and deploy your Python supercharged Notebooks and track the quality of your data using Machine learning. | 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. |
Develop, share and deploy your supercharged Python notebooks on a scalable platform;
Automate and streamline your workflows with Python-based data pipelines that leverage the power of notebooks;
Establish processes to measure and track the quality of your data over the time using machine learning | 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 1 | Followers 7 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Mineo, Kaggle?
Jupyter
The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.
Apache Zeppelin
A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.
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.
Deepnote
Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore and analyze it with real-time collaboration and versioning, and easily share and present the polished assets to end users.
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!
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.
AI Video Generator
Create AI videos at 60¢ each - 50% cheaper than Veo3, faster than HeyGen. Get 200 free credits, no subscription required. PayPal supported. Start in under 2 minutes.
