Machine Learning – Traditional model building process

  1. Identify the ML problem type: Regression, Classification or Time-Series
  2. Specify the data source and format of the labelled training data
  3. Choose your target variable or what you want to predict
  4. Train & Evaluate 100s of Machine Learning algorithms*
  5. Deploy, make predictions & generate insights**

*mltrons Automated Machine Learning curates state-of-the-art libraries like AutoKeras, PyTorch, TensorFlow, H2O, TPOT, Caffe, SageMaker, and AlphaD3M to build the best fit model for the data. Mltrons also provides GPUs to handle larger amount of data.

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