Dr. James McCaffrey of Microsoft Research presents the first in a series of four machine learning articles that detail a complete end-to-end production-quality example of neural regression using PyTorch.
- By James McCaffrey
- 02/02/2021
Dr. James McCaffrey of Microsoft Research continues his four-part series on multi-class classification, designed to predict a value that can be one of three or more possible discrete values, by explaining model accuracy.
- By James McCaffrey
- 01/25/2021
Dr. James McCaffrey of Microsoft Research continues his four-part series on multi-class classification, designed to predict a value that can be one of three or more possible discrete values, by explaining neural network training.
- By James McCaffrey
- 01/04/2021
Dr. James McCaffrey of Microsoft Research explains how to define a network in installment No. 2 of his four-part series that will present a complete end-to-end production-quality example of multi-class classification using a PyTorch neural network.
- By James McCaffrey
- 12/15/2020
Dr. James McCaffrey of Microsoft Research kicks off a four-part series on multi-class classification, designed to predict a value that can be one of three or more possible discrete values.
- By James McCaffrey
- 12/04/2020
In the final article of a four-part series on binary classification using PyTorch, Dr. James McCaffrey of Microsoft Research shows how to evaluate the accuracy of a trained model, save a model to file, and use a model to make predictions.
- By James McCaffrey
- 11/24/2020
Dr. James McCaffrey of Microsoft Research continues his examination of creating a PyTorch neural network binary classifier through six steps, here addressing step No. 4: training the network.
- By James McCaffrey
- 11/04/2020
Dr. James McCaffrey of Microsoft Research tackles how to define a network in the second of a series of four articles that present a complete end-to-end production-quality example of binary classification using a PyTorch neural network, including a full Python code sample and data files.
- By James McCaffrey
- 10/14/2020
Dr. James McCaffrey of Microsoft Research kicks off a series of four articles that present a complete end-to-end production-quality example of binary classification using a PyTorch neural network, including a full Python code sample and data files.
- By James McCaffrey
- 10/05/2020
Dr. James McCaffrey of Microsoft Research provides a full code sample and screenshots to explain how to create and use PyTorch Dataset and DataLoader objects, used to serve up training or test data in order to train a PyTorch neural network.
- By James McCaffrey
- 09/10/2020
Dr. James McCaffrey of Microsoft Research explains how to programmatically split a file of data into a training file and a test file, for use in a machine learning neural network for scenarios like predicting voting behavior from a file containing data about people such as sex, age, income and so on.
- By James McCaffrey
- 09/01/2020
Dr. James McCaffrey of Microsoft Research uses a full code program and screenshots to explain how to programmatically encode categorical data for use with a machine learning prediction model such as a neural network classification or regression system.
- By James McCaffrey
- 08/12/2020
Dr. James McCaffrey of Microsoft Research uses a full code sample and screenshots to show how to programmatically normalize numeric data for use in a machine learning system such as a deep neural network classifier or clustering algorithm.
- By James McCaffrey
- 08/04/2020
After previously detailing how to examine data files and how to identify and deal with missing data, Dr. James McCaffrey of Microsoft Research now uses a full code sample and step-by-step directions to deal with outlier data
- By James McCaffrey
- 07/14/2020
Turning his attention to the extremely time-consuming task of machine learning data preparation, Dr. James McCaffrey of Microsoft Research explains how to examine data files and how to identify and deal with missing data.
- By James McCaffrey
- 07/06/2020