Apply pre-designed algorithmic models to specified use cases
About
This unit is about applying a variety of pre-designed algorithmic models to specified use cases for internal and external clients.
Scope
define hypothesis, apply and optimize model
Define hypothesis
- identify the objective of the analysis
- evaluate the dataset to determine a suitable approach
- identify suitable libraries, packages, frameworks, applications to address the objective
Apply and optimize model
- select suitable algorithmic models from available statistical analysis softwares, packages, libraries or tools
- apply the model for various use cases and scenarios such as vision, text recognition, image recognition, natual language processing etc.
- optimize selected algorithmic models to resolve any shortcomings or defects
- iterate the model in consultation with relevant stakeholders till the desired performance or quality of output is achieved
- validate the models implemented using approporiate tools and processes
- create documentation on applied algorithmic models for future references and versioning
Required Knowledge & Understanding
Technical Skills
- different statistical analysis software, packages, libraries or tools with pre-designed algorithmic models such as Mahout, BigML, Data Robot, Knime, Tensorflow
- different programming languages that can be used to design algorithmic models such as python, ruby, C, java, c++, c# etc.
- different use cases and the suitability of various algorithmic models to address them
- how to build and test a hypothesis
- different cloud or distributed computing platforms such as AWS, Azure, Hadoop, their affiliated services and how to use these
- how to identify and refer anomalies in data
- how to work on various operating systems such as linux, ubuntu, or windows
Soft Skills
Core / Generic Skills
impact analysis of the various actions performed and disseminating relevant information to others. analyze data, models and understand its implications on business performance
Attention to Detail
check your work is complete and free from errors