In recent years, Kernel methods have received major attention, particularly due to the increased popularity of the Support Vector Machines. Kernel functions can be used in many applications as they provide a simple bridge from linearity to non-linear…
7 Machine Learning System Design Content 7 Machine Learning System Design 7.1 Prioritizing What to Work On 7.2 Error Analysis 7.3 Error Metrics for Skewed Classed 7.3.1 Precision/Recall 7.3.2 Trading off precision and recall: F1 Score 7.4 Data for ma…
Graph-powered Machine Learning at Google Thursday, October 06, 2016 Posted by Sujith Ravi, Staff Research Scientist, Google ResearchRecently, there have been significant advances in Machine Learning that enable computer systems to solve compl…
https://jmetzen.github.io/2015-01-29/ml_advice.html Advice for applying Machine Learning This post is based on a tutorial given in a machine learning course at University of Bremen. It summarizes some recommendations on how to get started with machin…
Practical Machine Learning For The Uninitiated Last fall when I took on ShippingEasy's machine learning problem, I had no practical experience in the field. Getting such a task put on my plate was somewhat terrifying, and even more so as we started t…
from: http://www.erogol.com/broad-view-machine-learning-libraries/ http://www.slideshare.net/VincenzoLomonaco/deep-learning-libraries-and-rst-experiments-with-theano FEBRUARY 6, 2014 EREN 1 COMMENT Especially, with the advent of many different and in…
A Gentle Introduction to the Gradient Boosting Algorithm for Machine Learning by Jason Brownlee on September 9, 2016 in XGBoost 0 0 0 0 Gradient boosting is one of the most powerful techniques for building predictive models. In this post you will d…
8 Tactics to Combat Imbalanced Classes in Your Machine Learning Dataset by Jason Brownlee on August 19, 2015 in Machine Learning Process Has this happened to you? You are working on your dataset. You create a classification model and get 90% accuracy…
