Accelerate the return on investment of your data science initiatives without depending on complex data pipelines.
You can achieve that by automating the entire data science flow: algorithm, feature sets, models, training, test, validation, monitoring, continuous check and improvement. It will make data scientists spend more time focused on their core activity, spending less effort to understand and prepare data for analysis.
Follow up on your machine learning model in a production environment in a platform that allows automated training to ensure high-quality new ideas.
