Here's a hands-on tutorial from bona-fide data scientist Dr. James McCaffrey of Microsoft Research to get you up to speed with machine learning development using C#, complete with code listings and graphics.
- By James McCaffrey
- 11/07/2019
Microsoft Research's Dr. James McCaffrey show how to perform binary classification with logistic regression using the Microsoft ML.NET code library. The goal of binary classification is to predict a value that can be one of just two discrete possibilities, for example, predicting if a person is male or female
- By James McCaffrey
- 10/18/2019
Dr. James McCaffrey provides hands-on examples in introducing ML.NET, for machine learning prediction models, and AutoML, which automatically examines different ML algorithms, finds the best one, and creates a Visual Studio project with the C# code backing the best model, along with C# code that shows how to use the trained model to make a prediction.
- By James McCaffrey
- 09/30/2019
Microsoft Research data scientist Dr. James McCaffrey explains what neural network Glorot initialization is and why it's the default technique for weight initialization.
- By James McCaffrey
- 09/05/2019
Data scientist Dr. James McCaffrey begins a series on presenting and explaining the most common modern techniques used for neural networks, for which over the past couple of years there have been many small but significant changes in the default techniques used.
- By James McCaffrey
- 07/29/2019
Suppose you have three different Internet advertising strategies and you want to determine which of them is the best as quickly as possible. Or suppose you work for a medical company and you want to determine which of three new drugs is the most effective. Resident data scientist Dr. James McCaffrey shows how Thompson Sampling can help.
- By James McCaffrey
- 07/25/2019
Dr. James McCaffrey of Microsoft Research uses Python code samples and screenshots to explain naive Bayes classification, a machine learning technique used to predict the class of an item based on two or more categorical predictor variables, such as predicting the gender (0 = male, 1 = female) of a person based on occupation, eye color and nationality.
- By James McCaffrey
- 05/14/2019
Need to predict the political party affiliation (democrat, republican, independent) of a person based on their age, annual income, gender, years of education and so on? Our resident data scientist Dr. James McCaffrey shows a technique that can help with that and much more -- with code!
- By James McCaffrey
- 04/10/2019
Our resident doctor of data science this month tackles anomaly detection, using code samples and screenshots to explain the process of finding rare items in a dataset, such as discovering fraudulent login events or fake news items.
- By James McCaffrey
- 03/04/2019
The Data Science doctor delves into supporting vector machines, software systems that can perform binary classification such as creating a model to predict the gender of a person based on their age, annual income, height and weight.
- By James McCaffrey
- 03/04/2019
Dr. James McCaffrey of Microsoft Research uses a full project code sample and screenshots to detail how to use Python to work with self-organizing maps (SOM), which let you investigate the structure of a set of data.
- By James McCaffrey
- 01/15/2019
Creating a custom image classification model is challenging, but the existence of neural network libraries like Keras has made it doable. Here's how, with many code samples and a full project download.
- By James McCaffrey
- 01/02/2019
Custom sentiment analysis is hard, but neural network libraries like Keras with built-in LSTM (long, short term memory) functionality have made it feasible. Step into the Data Science Lab with Dr. McCaffrey to find out how, with full code examples.
- By James McCaffrey
- 11/15/2018
The Data Science Doctor explains how to use the reinforcement learning branch of machine learning with the Q-learning approach, providing code on how to solve a maze problem for an easy-to-understand example.
- By James McCaffrey
- 10/19/2018
Our resident data scientist provides a hands-on example on how to make a prediction that can be one of just two possible values, which requires a different set of techniques than classification problems where the value to predict can be one of three or more possible values.
- By James McCaffrey
- 08/30/2018