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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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.

October 2017 / 14:21 min

Learn how BigML Deepnets help you automatically find the best neural network to solve classification and regression problems.

July 2017 / 10:11 min

Learn how to analyze time-ordered historical data to forecast future behavior using BigML 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 Clusters.

July 2017 / 8:17 min

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

July 2017 / 28:13 min

Learn how to find statistically significant rules in your data using BigML 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.

February 2018 / 14:14 min

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

October 2018 / 10:38 min

Learn how BigML organizations provide granular team and project management capabilities, making BigML a transparent, collaborative platform for all members of your corporation.

October 2018 / 23:30 min

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.