Machine learning is already here and has been applied by businesses already. Massive computing power has become inexpensive and is being used by machine learning to run predictive models which fetch details from existing data in order to detect fraud, demand forecasting or ad targeting. Machine learning offers lots of benefits to business which includes rapid processing, analysis, predictions, etc. It provides the capability to deliver new products and services by lowering the cost of existing products.
We provide the following services with respect to Machine Learning:
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Algorithm Design. Our expert engineers have an analytical and methodological approach to solve problems which are relative while designing or writing effective algorithms. We have an appropriate set of technologies to optimize existing algorithms for any given situation.
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Data Modelling. We offer your business a complete data modeling solution right from hypothesizing to the physical implementation of the data model. Our tools are able to extract thorough requirements related to your business by providing you with a complete solution.
We will be happy to build your own ML ecosystem either from scratch or on top of leading platforms, such as:
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Amazon Machine Learning. It provides visualization tools and wizards which can assist you in creating machine learning models without learning complex ML algorithms. It is an easy process to generate the forecasts of your applications by using Amazon ML APIs, without implementing custom prediction generation code or managing any infrastructure.
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Microsoft Azure Machine Learning. It is a cloud-based predictive analysis service utilized by Taskdata for creating and deploying predictive models as analytics solutions.
Taskdata also provides Machine Learning as a Service with a library of machine learning algorithms well-connected to visualization tools, accelerating time to insights. The service includes machine learning techniques to predict KPIs, prepare data, exploratory analytics, feature extraction, modelling, validation, pilot and full-scale implementation.