-
Must-Know: How to determine the most useful number of clusters?
Without knowing the ground truth of a dataset, then, how do we know what the optimal number of data clusters are? We will have a look at 2 particular popular methods for attempting to answer this question: the elbow method and the silhouette method.
-
 Deep Learning in Minutes with this Pre-configured Python VM Image
Check out this Python deep learning virtual machine image, built on top of Ubuntu, which includes a number of machine learning tools and libraries, along with several projects to get up and running with right away.
-
The Guerrilla Guide to Machine Learning with Python
Here is a bare bones take on learning machine learning with Python, a complete course for the quick study hacker with no time (or patience) to spare.
-
More Deep Learning “Magic”: Paintings to photos, horses to zebras, and more amazing image-to-image translation
This is an introduction to recent research which presents an approach for learning to translate an image from a source domain X to a target domain Y in the absence of paired examples.
-
 5 Machine Learning Projects You Can No Longer Overlook, April
By Matthew Mayo, KDnuggets Managing Editor on April 13, 2017 in Data Exploration, Deep Learning, Java, Machine Learning, Neural Networks, Overlook, Python, Scala, scikit-learn, Topic ModelingIt's about that time again... 5 more machine learning or machine learning-related projects you may not yet have heard of, but may want to consider checking out. Find tools for data exploration, topic modeling, high-level APIs, and feature selection herein.
-
 10 Free Must-Read Books for Machine Learning and Data Science
Spring. Rejuvenation. Rebirth. Everything’s blooming. And, of course, people want free ebooks. With that in mind, here's a list of 10 free machine learning and data science titles to get your spring reading started right.
-
A Beginner’s Guide to Tweet Analytics with Pandas
Unlike a lot of other tutorials which often pull from the real-time Twitter API, we will be using the downloadable Twitter Analytics data, and most of what we do will be done in Pandas.
-
17 More Must-Know Data Science Interview Questions and Answers, Part 3
By Matthew Mayo, KDnuggets Managing Editor on March 15, 2017 in 3Vs of Big Data, A/B Testing, Big Data, Data Quality, Data Science, Data Visualization, Influencers, Interview Questions, Statistics, TwitterThe third and final part of 17 new must-know Data Science interview questions and answers covers A/B testing, data visualization, Twitter influence evaluation, and Big Data quality.
-
Toward Increased k-means Clustering Efficiency with the Naive Sharding Centroid Initialization Method
What if a simple, deterministic approach which did not rely on randomization could be used for centroid initialization? Naive sharding is such a method, and its time-saving and efficient results, though preliminary, are promising.
-
7 More Steps to Mastering Machine Learning With Python
By Matthew Mayo, KDnuggets Managing Editor on March 1, 2017 in 7 Steps, Classification, Clustering, Deep Learning, Ensemble Methods, Gradient Boosting, Machine Learning, Python, scikit-learn, Sebastian RaschkaThis post is a follow-up to last year's introductory Python machine learning post, which includes a series of tutorials for extending your knowledge beyond the original.
|
Deep Learning in Minutes with this Pre-configured Python VM Image
5 Machine Learning Projects You Can No Longer Overlook, April
10 Free Must-Read Books for Machine Learning and Data Science
17 More Must-Know Data Science Interview Questions and Answers, Part 3
7 More Steps to Mastering Machine Learning With Python