Machine Learning for Minimum Viable Model (MVM) helps customers develop an initial machine learning model running on TensorFlow to demonstrate PoC modeling of a specific business use case. We will guide you on the iterative process for developing an initial model that demonstrates the feasibility of a solution addressing a business use case.
How we do it
Data Exploration Guidance
Analyze available data sources to assess the state of data and potential usefulness in applying in an ML model, including analysis of data characteristics, data quality, cleanliness, potential correlation, and patterns. Check for class imbalance and validate hypotheses relative to data.
Research modeling strategies to determine the appropriate ML selection algorithm to address business problems, including research existing strategies and whitepapers. We’ll help to select known algorithms based on hypothesis, type of features, patterns in data.
Create ML model features based on raw data analysis and tests using the domain knowledge to identify potential features and advice on the transformation of raw data into feature recommendations.
Initial Model Development
Develop an initial ML model using the data to solve the business problem, and iterate.
Preliminary machine learning model through an iterative process.