DS/ ML/ Analytics
Data Science Expertise & Methodology
Services

Result-As-A-Service
Provide your data and receive the results

Analytics Advisory
Develop and implement solutions

Analytics Workshops
Identify business problems to be solved

Managed Services
Dedicated services and support hosted at our location

Analytics Testing
Third party products and solutions validation
Machine Learning

Supervised Learning
In this method, the input and output as well as feedback during training will be provided to the system. It also analyzes the accuracy of the system’s prediction during the training process. The main purpose of training is to make the system learn how to map an input to output.

Unsupervised Learning
In this case, no such training is provided, and the system is allowed to find the output on its own. Unsupervised learning is mainly applied to transaction data. It is used for more complex tasks. It uses another iterative method called deep learning to draw some conclusions.

Reinforcement Learning
Reinforcement learning is different from the other types of supervised learning because the system doesn’t need any labeled input-output pairs. Alternatively, the system finds the best possible policy through trial and error.