Machine Learning Pipeline plug & play solution for the customer journey and price optimization analytics that works as a cloud-native solution.

Data cleaning has been a long-unsolved challenge that has plagued the data science and analytics industry. Data scientists spend numerous hours preparing their data for modeling. B2Metric AI brings automatically data preparation feature for data scientists. Together with this developing technology, it has taken the new developments and technology data gathering & cleaning process to an advanced and higher-level providing users a new perspective and high level of experience. Data scientists and analysts achieve this with a click of a button.

Building machine learning models can often be a complex and boring process and it involves many steps. So, B2Metric ML Studio is able to automate a certain percentage of feature engineering tasks, then the data scientists or the domain experts can focus on other aspects of the model. Automated feature engineering helps on time saving, building better predictive models, creating meaningful features and preventing leakage of datas. At the same time, the datas are prepared by B2Metric AI to automatically modeling, to execute operations like one-hot encoding, missing data imputation, text mining, standardization and data partitioning.

If this has to be done by hand this would have taken several days, yet with automated machine learning, this only took hardly any hours. The key strength of the automated feature engineering is when it’s applied to regrouping or reshaping data. This is why it is recommended that engaging the creativity and experience of business domain experts for domain-specific feature knowledge, such as how to correctly interpret the data.

The process of automating the wasteful time, iterative jobs of machine learning model development is called automated machine learning, also referred to as autoML. It permits analysts, data scientists, and developers to build ML models with high scale, efficiency, and productivity all while sustaining model quality. B2Metric AI main technology got the basis of autoML. Automated machine learning is the works of automating the end-to-end process of applying machine learning to complex real-world problems. B2Metric AutoML makes machine learning available in the right sense, even to people with no major expertise in this field.

The traditional way of ML model development process is a resource and labor-intensive, requiring critical domain expertise and time to produce and compare dozens of models. Apply automated ML when you want B2Metric Machine Learning to train and tune a model for you using the target metric you specify.

Manually finding the right algorithm and tuning it to fit your dataset, well is a challenging task. B2Metric AI technology automates the algorithm selection and hyperparameter optimization on algorithms ranging from classical scikit-learn algorithms to complex time series algorithms. Every model built-in B2Metric AI can be put into production straight away. You can upload data to be scored in bundles. Monitor the performance of all deployed models from a central portal, and easily refresh and replace models if data and accuracy changes over time.

Model deployments on the data stream and the predictions are live and on the spot. You can deploy on a dynamic B2Metric AI that enables you to watch real-time updates from dashboards. If no ready-made AI service are available off-the-rack, that does not mean you have to build everything from the ground up with libraries. There is a middle ground: customizable AI and ML models that you can train with your own data. In this way, you can save more time and money. Thus, you can make and expect a faster and as well healthier decision than the feedback you need. As a result, you can integrate it into your own product using APIs.

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