Frontier — An Analytics Workbench by FluidAI

  • Data Fetching
  • Data Cleaning
  • Data Visualization
  • Feature Extraction
  • Feature Engineering
  • Model Training
  • Predictions
  • Environment Friendly: Frontier can be deployed in Cloud or as an on-premise server offering flexibility to organizations all across.
  • Projects and Versioning: This feature allows the user to create multiple projects and have multiple versions of Model in it.
  • Pipelines: Pipelines are predefined data flows to ensure a particular outcome to User. Frontier allows creation of multiple pipelines for a specific project and there are a few important ones which come with the product itself such as:

    - Database Pipelines: Users can connect to various databases such MySQL, MsSQL, Oracle, Snowflake and MongoDB in just a few steps. Using SQL statements data can be fetched from the databases directly and stored as csv files.
    - Data Vectorization: Data as we know requires Feature Engineering to be fed to AI models, frontier also takes care of that. Various techniques such as Standardization, Normalization and One-Hot Encoding are available at your fingertips to make things easier.
    - Model Training: Model Training is now easier than ever as one can select the training features and the target variable after vectorization with choice of appropriate algorithm and BINGO!.
  • Reports and Visualizations: Not all of us want to generate predictions without knowing how the Data looks like, well we’ve got that covered as well. We understand that Data Visualization is a very underrated and a vital technique so we’ve got 9 kinds of Charts such as Bar Chart, Line Chart and Pie Chart to name a few.
  • Model Registry: All the models can be found on one page so that you don’t have to keep looking for a model you trained months back. Here, you can also find the metrics corresponding to each model i.e. Precision, Recall, RMSE, MAE, F2-Score, Silhouette Score, Inertia etc. To make things easier for all the developers around we have introduced features such as exposing the Model as an API and generating Data Drift Report.
  • Jupyter Notebooks: Well to all the Developers and Data Scientists, we know that we all have our trust issues and we’d rather write code ourselves. We all love Jupyter Notebooks and know how essential they are. So, we also have a Jupyter Notebook Server which comes along with the Product and it will have access to all the project data. Have a look !



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