What are the examples of No-code ML?
No-code Machine Learning have many examples and tools for training and deployment of the model with small coding expertics
- Google Cloud AutoML: Google Cloud AutoML is providing the user user-friendly interface and allows users to train high-quality custom machine learning models. It is also providing several products,like AutoML Vision, AutoML Natural Language, and AutoML Tables, which give users to develop models for image recognition, text analysis, and structured data classification without writing code.
- RapidMiner: RapidMiner is a visual workflow-based data science platform which have no-code machine learning capabilities. It give users to create and execute end-to-end data pipelines for tasks such as data preprocessing, model training, and evaluation.
What is No-Code Machine Learning?
As we know Machine learning is a field in which the data are provided according to the use case of the feature engineering then model selection, model training, and model deployment are done with programming languages like Python and R. For developing the model the person or developer must have the data science domain for implementation. to overcome this problem of knowing the domain users are No-code Machine Learning is a machine learning approach that implements user ideas for building the model who don’t have any knowledge of coding to build, train, and deploy different machine learning models. No Code ML platforms feature intuitive graphical user interfaces that allow users to interact with the tools without coding skills.
In this article, we will explore No-Code Machine Learning , Features of no-code machine learning , Difference between traditional and no-code machine learning , Use of No-code ML across industries.