The Flek Machine streamlines multiple activities into one end-to-end database-like ML pipeline.
ML Pipeline
Flek ML pipeline consists of a sequence of integrated activities. When used together, they form an end-to-end machine learning workflow that starts with data preparation and ends with prediction and recommendation:
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Encode & Load. Prepare the raw data and upload it into the ML engine
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Build. Learn the probabilistic model and store the Nuggets using core ML algorithms
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Query. Fetch the stored Nuggets from the engine
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Mine. Iteratively scan the model store for Nuggets with given signature
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Explore. Search for probabilistic patterns, visualize, tabulate, trace and validate
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Discover. Auto-discover interesting associations, rules, anomalies or causal relationships
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Predict. Run both forward and backward prediction and classification activities
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Recommend. Perform both profile and item based recommendation tasks