From medical diagnosis, speech, and handwriting recognition to automated trading and movie recommendations, machine learning techniques are being used to make critical business and life decisions every moment of the day. Each problem is unique, so it can be challenging to manage raw data, identify the right data to include in the model, train multiple types of models, and perform model assessments. Machine learning uses algorithms that learn from data to help make better decisions; however,it is not always obvious what the best machine learning algorithm is going to be for a particular problem. Luckily, information such as variable importance and model assessment tools can help us decide which machine learning techniques to apply. Examples of machine learning techniques include clustering, where objects are grouped into bins with similar traits; regression, where relationships among variables are estimated; and classification, where a trained model is used to predict a categorical response.

Machine learning was the fifth and latest guide. And now I'm back to conclude this series with even more resources. For each of the five major guides in this series, I spent several hours trying to identify every online course for the subject in question, extracting key bits of information from their syllabi and reviews, and compiling their ratings. My goal was to identify the three best courses available for each subject and present them to you. The 13 supplemental topics -- like databases, big data, and general software engineering -- didn't have enough courses to justify full guides. But over the past eight months, I kept track of them as I came across them. I also scoured the internet for courses I may have missed. For these tasks, I turned to none other than the open source Class Central community, and its database of thousands of course ratings and reviews.

As artificial intelligence proliferates, companies and governments are aggregating enormous data sets to feed their AI initiatives. Although privacy is not a new concept in computing, the growth of aggregated data magnifies privacy challenges and leads to extreme ethical risks such as unintentionally building biased AI systems, among many others. Privacy and artificial intelligence are both complex topics. There are no easy or simple answers because solutions lie at the shifting and conflicted intersection of technology, commercial profit, public policy, and even individual and cultural attitudes. Given this complexity, I invited two brilliant people to share their thoughts in a CXOTALK conversation on privacy and AI.

The rise of Artificial Intelligence (AI) technology could be set to shake up the job scene in the UK sooner than expected, new research shows. A BT survey of over 1,500 senior UK IT decision makers found that AI, widely expected to usher in the "fourth industrial revolution," is in fact already splitting opinions in the labor market. On the positive side, a third of businesses which say they plan to introduce AI or automation technologies within the next two years believe it will create more jobs within the workplace. However, a similar amount of respondents also feared that implementing such services would lead to job losses, as robotic or automated procedures replaced trained human workers. Overall, one in four of the organizations surveyed say they are already using automation technologies, with the likes of drones, robots or autonomous vehicles proving popular.

Lecture 17 looks at solving language, efficient tree-recursive models SPINN and SNLI, as well as research highlight "Learning to compose for QA." Also covered are interlude pointer/copying models and sub-word and character-based models. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component. For additional learning opportunities please visit: http://stanfordonline.stanford.edu/

Artificial intelligence has already proven its worth at performing routine tasks. But how good can it be at artistic creativity? A group of researchers at Kingston University and Queen Mary University of London are exploring the concept with AI that composes music. According to Dr. Oded Ben-Tal, lead researcher and senior lecturer in music technology at Kingston University, the results are impressive and can mark a new chapter in music, in which humans and machines collaborate in creating art. There are practical reasons to start with Irish music, Ben-Tal said, including the availability of data.

Rawi will present these ideas during a live webinar on May 24th at 9 AM PT / 12 PM ET. Get your questions answered in real-time during this one hour event. We create, interpret, and experience stories every day, whether we realize it or not. Our brains are constantly receiving input and stringing things together in order for us to make sense of the world. While our brains create countless stories, only the few great ones stay with us.

The vast majority of software development books, whether it be for line-of-business app dev or game development, seem to have little to no information that can be found via a casual internet search. This book is one of the few exceptions. There is a refreshing breadth and depth of game AI knowledge in this book that has been of tremendous help. Unlike the common "Gems" series of books, this book contains enough information on nearly every topic for the reader to build a'ground up' implementation of their own. My only complaints are that the pseudocode seems to be overly simplified and not as easily converted to a concrete implementation as I'd like, and that even for a book on game-specific AI implementations, the authors seem to enjoy a bit more of an academic/idealized approach to the design.

Men should turn on their Playstation if they want to last longer in bed, new research shows. Those who play games for an hour each day are less likely to ejaculate prematurely - which can be embarrassing for men. However, it's not because gamers possess superior skills when it comes to making love, Italian researchers said. Instead, it is more likely because of their reduced desire, caring less about having a passionate night beneath the sheets. How was the study carried out?