Kaggle vs PyXLL
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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! | 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. |
User Defined Functions: Write Excel worksheet functions in Python - no VBA required;Ribbon Customization: Give your users a rich Excel native experience;Macros: No need for VBA, access to the full Excel Object Model in Python;Menu Functions: Call Python functions from Excel menus, and give common tasks keyboard shortcuts;Real Time Data: Stream data to Excel in real-time using Python;Array Functions: Return tables of data to Excel that resize automatically;IntelliSense: Auto-complete worksheet functions as you type them;NumPy and Pandas Integration: Use NumPy and Pandas types in Excel | 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 8 | Stacks 10 |
Followers 104 | Followers 7 |
Votes 8 | Votes 0 |
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What are some alternatives to PyXLL, 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
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.
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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