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 to 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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June 2017 / 8:03 min

Take a brief tour of the BigML interface. Learn how to work with resources and navigate the BigML Dashboard.

June 2017 / 16:55 min

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.

June 2017 / 36:34 min

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.

July 2017 / 7:24 min

Learn the differences between Supervised and Unsupervised Machine Learning techniques.

June 2017 / 8:06 min

Learn the basics of supervised learning Models and how to create and understand Decision Trees.

June 2017 / 8:50 min

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.

June 2017 / 8:03 min

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.

June 2017 / 37:20 min

Learn how to configure and interpret Logistic Regression models to solve classification problems.

July 2017 / 10:11 min

Learn how to analyze time-ordered historical data to forecast future behavior using BigML's Time Series.

August 2017 / 9:09 min

Learn how and why you should evaluate the performance of your supervised models before making predictions.

July 2017 / 27:17 min

Learn how to separate your data into groups of similar instances using BigML's Clusters.

July 2017 / 8:17 min

Learn how to identify unusual instances in your data using BigML's Anomaly Detector.

July 2017 / 28:13 min

Learn how to find statistically significant rules in your data using BigML's Association Discovery.

July 2017 / 11:40 min

Learn how to process natural language using Topic Models to automatically discover relevant relationships.

June 2017 / 5:51 min

Learn how to use Decision Trees, Ensembles, or Logistic Regression to make individual Predictions or generate Batch Predictions for a group of new instances.

August 2017 / 43:47 min

Learn how to engineer new features and filter your datasets with Flatline.