BigML Education Videos
BigML offers a wide variety of basic Machine Learning resources that can be composed together to solve complex Machine Learning tasks. You can access those resources via the BigML Dashboard, an intuitive web-based interface, or programmatically via its REST API or a multitude of libraries and tools. The introductory videos below will help you get up to speed with the BigML Dashboard regardless if you have any prior background in Machine Learning.
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Take a brief tour of the BigML interface. Learn how to work with resources and navigate the BigML Dashboard.
Sources are the first step of any BigML workflow. Learn the basic features of BigML Sources, including file formats and upload options, or advanced parsing configuration options.
Datasets are the fundamental building block for your BigML workflows. Learn how to filter, sample, add new fields, or split a dataset into training and test datasets.
Learn the differences between Supervised and Unsupervised Machine Learning techniques.
Learn the basics of supervised learning Models and how to create and understand Decision Trees.
Learn more about solving supervised learning problems using BigML. This tutorial uses a loan dataset to explain the sunburst view and how to deal with unbalanced datasets.
Learn how to create and parametrized Ensembles and how to interpret them using the Partial Dependence Plot (PDP) or the Field Importance Report provided by BigML.
Learn how to configure and interpret Logistic Regression models to solve classification problems.
Learn how BigML Deepnets help you automatically find the best neural network to solve classification and regression problems.
Learn how to analyze time-ordered historical data to forecast future behavior using BigML Time Series.
Learn how and why you should evaluate the performance of your supervised models before making predictions.
Learn how to separate your data into groups of similar instances using BigML Clusters.
Learn how to identify unusual instances in your data using BigML Anomaly Detector.
Learn how to find statistically significant rules in your data using BigML Association Discovery.
Learn how to process natural language using Topic Models to automatically discover relevant relationships.
Learn how to use Decision Trees, Ensembles, or Logistic Regression to make individual Predictions or generate Batch Predictions for a group of new instances.
Learn how to engineer new features and filter your datasets with Flatline.
Take a brief tour of the BigML interface in Chinese. Learn how to work with resources and navigate the BigML Dashboard in Chinese.
Learn how BigML organizations provide granular team and project management capabilities, making BigML a transparent, collaborative platform for all members of your corporation.
Learn about OptiML, the automatic optimization feature for model selection and parameterization on BigML. OptiML helps you avoid the difficult and time-consuming work of hand-tuning multiple supervised algorithms until you find the best one that solves your specific problem.
