转自:http://www.cleverhans.io/security/privacy/ml/2017/02/15/why-attacking-machine-learning-is-easier-than-defending-it.html Is attacking machine learning easier than defending it? Feb 15, 2017 by Ian Goodfellow and Nicolas Papernot In our first post…
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…
原文:http://googleresearch.blogspot.jp/2010/04/lessons-learned-developing-practical.html Lessons learned developing a practical large scale machine learning system Tuesday, April 06, 2010 Posted by Simon Tong, Google Research When faced with a hard pre…
https://www.quora.com/How-do-I-learn-machine-learning-1?redirected_qid=6578644 How Can I Learn X? Learning Machine Learning Learning About Computer Science Educational Resources Advice Artificial Intelligence How-to Question Learning New Things Lea…
https://www.quora.com/How-do-I-learn-mathematics-for-machine-learning How do I learn mathematics for machine learning? Promoted by Time Doctor Software for productivity tracking. Time tracking and productivity improvement software with screenshots…
About this Course You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been…
About this Course Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly i…
##Linear Regression with One Variable Linear regression predicts a real-valued output based on an input value. We discuss the application of linear regression to housing price prediction, present the notion of a cost function, and introduce the gradi…
##Advice for Applying Machine Learning Applying machine learning in practice is not always straightforward. In this module, we share best practices for applying machine learning in practice, and discuss the best ways to evaluate performance of the le…
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…
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…
Why The Golden Age Of Machine Learning is Just Beginning Even though the buzz around neural networks, artificial intelligence, and machine learning has been relatively recent, as many know, there is nothing new about any of these methods. If so many…
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…
ON THE EVOLUTION OF MACHINE LEARNING: FROM LINEAR MODELS TO NEURAL NETWORKS We recently interviewed Reza Zadeh (@Reza_Zadeh). Reza is a Consulting Professor in the Institute for Computational and Mathematical Engineering at Stanford University and a…
Common Pitfalls In Machine Learning Projects In a recent presentation, Ben Hamner described the common pitfalls in machine learning projects he and his colleagues have observed during competitions on Kaggle. The talk was titled "Machine Learning Grem…
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…
Teaching Your Computer To Play Super Mario Bros. – A Fork of the Google DeepMind Atari Machine Learning Project Posted by ehrenbrav on August 25, 2016Leave a comment (14)Go to comments For those who want to get right to the good stuff, the installa…
转自:机器学习(Machine Learning)&深度学习(Deep Learning)资料 <Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机.神经网络.决策树.SVM.Adaboost到随机森林.Deep Learning. <Deep Learning in Neural Networks: An Overview> 介绍:这是瑞士人工智能实验室Jurgen Schmidhuber写的最…
Machine Learning for Developers Most developers these days have heard of machine learning, but when trying to find an 'easy' way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learnin…
What is machine learning? One area of technology that is helping improve the services that we use on our smartphones, and on the web, is machine learning. Sometimes, the terms machine learning and artificial intelligence get used as synonyms, especia…
Seven Steps to Success Machine Learning in Practice Project failures in IT are all too common. The risks are higher if you are adopting a new technology that is unfamiliar to your organisation. Machine learning has been around for a long time in acad…
In the first installment of this series, we scraped reviews from Goodreads. In thesecond one, we performed exploratory data analysis and created new variables. We are now ready for the "main dish": machine learning! Setup and general data prep L…
In my last article, I stated that for practitioners (as opposed to theorists), the real prerequisite for machine learning is data analysis, not math. One of the main reasons for making this statement, is that data scientists spend an inordinate amoun…
Targeted learning methods build machine-learning-based estimators of parameters defined as features of the probability distribution of the data, while also providing influence-curve or bootstrap-based confidence internals. The theory offers a general…
