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Dataset Preparation for Machine Learning: Faster With Artifician
Data preparation is the most time-consuming and least enjoyable task for artificial intelligence (AI) developers (Forbes, 2016). But that's about to change. How? Plato Solutions has designed a tool that will allow you to do that job more easily and in less time: Artifician. What is this solution and how can it make your job easier?
Here we answer these questions.
What Is Artifician?
Artifician is a Python library developed to speed up and simplify the process of dataset preparation for AI models. Machines do not understand information in the same way that humans do. Therefore, Artifician takes out the burden of processing the raw data to machine-understandable format helping you to focus more on developing the model rather than building the dataset.
- Saves up time – Data scientists and machine learning (ML) engineers spend 80% of their time preparing the dataset for their AI models. That's too much! With Artifician you will save up to 50% of that time. Also, you will take more advantage of CPU resources with its multi-threading architecture, which makes the process faster than other dataset preparation tools.
- Fewer lines of code – Processing raw data is a tedious task. The longer your code is, the more complex it becomes to work with. However, Artifician has a set of predefined processors or utilities that will help you during preprocessing and postprocessing of data, shortening the lines of code considerably. Of course, since it is an open-source library, developers will be able to expand those utilities according to their needs.
- Makes code more readable and easy to manage – Your code should tell a story and be easy to understand and follow for anyone who reads it. Artifician has a decoupled architecture that will allow you to have not only more organized and readable code but also easier to modify and manage. So now you will no longer need to make changes at multiple places to add or remove features.
Artifician is a powerful and fast tool that will help you during data preparation. You will save time and write more readable and easy-to-manage code with fewer lines. Why don't you give it a test? Take a look at Artifician's documentation and let us know in the comments below what you think.