Machine Learning Using C# Succinctly marks the 50th e-book in the Succinctly series! We’ve shared some high-fives in the office to celebrate this milestone, and though we aren’t able to high-five you, dear reader, we do hope you will download the e-book. We’ll consider the two equivalent.
Machine Learning Using C# Succinctly was written by James McCaffrey, who also contributed Neural Networks Using C# Succinctly to the Succinctly series earlier this year. In his newest book, McCaffrey explores several different approaches to analyzing and predicting data using machine learning techniques, depending on whether the problem involves strictly numeric data, qualitative data, or a mix of both.
Machine Learning Using C# Succinctly
Techniques demonstrated in the book include k-means clustering, categorical data clustering, logistic regression classification, naïve Bayes classification, and neural network classification. So whether you’re facing a problem that requires you to group similar data to identify patterns, or predict which group new data belongs to, you’ll find a machine learning technique you can experiment with.
Since February of this year, we’ve doubled the number of e-books in the Succinctly series. We are really proud of this awesome accomplishment and the amount of information we’ve been able to share in such a short period of time. And, although we can’t promise our series will continue to grow on a Moore’s law scale, we can guarantee Syncfusion will continue publishing quality work each month, written by experts you can trust on topics that matter most to developers.
Fans of the Succinctly series
So, if you haven’t checked out the complete Succinctly series in a while, you definitely should. There’s bound to be a title that will make you think, “I really need to look into that,” whether you’re looking for a new web framework to try, an intro to functional programming, or a programming language for statistical analysis. All we ask is that you keep reading, keep learning, and keep building.
If the Succinctly series has helped you expand your skill set, let us know on Facebook and Twitter. And if there are specific topics you’d like to see added to the series, feel free to email us at firstname.lastname@example.org.