Monkey Learn + moonclerk Integrations

Monkey Learn?

MonkeyLearn is a machine learning platform that provides easy-to-use APIs to build applications that learn from data.

It allows users to easily create machine learning models using their own data and integrate them with their own apps.

Using MonkeyLearn, one can transform text into structured data and use them as features of machine learning algorithms.

moonclerk?

moonclerk is an open source package for R which allows the user to seamlessly integrate the Machine Learning algorithms provided by MonkeyLearn with moonclerk’s existing capabilities.

It allows the user to run machine learning algorithms such as text classification and tag extraction on text files directly from R.

Integration of Monkey Learn and moonclerk

The two packages provide a seamless integration so the user can easily train a machine learning model, use it with a specific task and access all the information about it within a single system. This is done via the fplowing steps:

• Train a model with Monkey Learn
• Export the model to moonclerk
• Use the model to complete a specific task in moonclerk
• View your results in a web interface with full information about the original file, the resulting data and the model used for processing it.

Benefits of Integration of Monkey Learn and moonclerk

moonclerk allows users to create applications which include machine learning without having to write a single line of code or learn complex libraries such as Scikit-learn or TensorFlow. These steps are done automatically by the package developers. Therefore, users can focus on writing code for their application instead of wasting time with coding for machine learning algorithms. The use of moonclerk saves time and money as there is no need to hire expensive programmers or purchase expensive software licenses for machine learning. Another benefit is that it allows users to quickly analyze their data without having to rely on huge databases or big computing power. It also allows them to do this easily from any desktop computer with limited memory and CPU power. Moreover, it allows them to do this without having to be an expert in machine learning algorithms. All these features allow users to quickly implement machine learning into their own applications without adding too much complexity or having to spend too much money. The result is that they can create applications that include machine learning even if they are not experts in it.

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