User intended actions are widely seen in many areas. Forecasting these actions and taking proactive measures to optimize business outcome is a crucial step towards sustaining the steady business growth. In this work, we focus on pre- dicting attrition, which is one of typical user intended actions. Conventional attrition predictive modeling strategies suffer a few inherent drawbacks. To overcome these limitations, we propose a novel end-to-end learning scheme to keep track of the evolution of attrition patterns for the predictive modeling. It integrates user activity logs, dynamic and static user profiles based on multi-path learning. It exploits historical user records by establishing a decaying multi-snapshot technique. And finally it employs the precedent user intentions via guiding them to the subsequent learning procedure. As a result, it addresses all disadvantages of conventional methods. We evaluate our methodology on two public data repositories and one private user usage dataset provided by Adobe Creative Cloud. The extensive experiments demonstrate that it can offer the appealing performance in comparison with several existing approaches as rated by different popular metrics. Furthermore, we introduce an advanced interpretation and visualization strategy to effectively characterize the periodicity of user activity logs. It can help to pinpoint important factors that are critical to user attrition and retention and thus suggests actionable improvement targets for business practice. Our work will provide useful insights into the prediction and elucidation of other user intended actions as well.

In this, the first in a two-part series, you will learn about artificial intelligence and machine learning, common missteps, success criteria, and how to take advantage of these new capabilities. A few years ago, machine learning was virtually unheard of outside the geek press; now it's blasted past cutting-edge to the top of the strategic agenda. In fact, in a recent study by SAP and the Economist Intelligence Unit, "Making the Most of Machine Learning: 5 Lessons from Fast Learners," 68% of companies surveyed are using machine learning in some form; among procurement companies, it is about 65%. These companies are on a path toward automation. Social psychologist and Harvard professor Shoshana Zuboff said, "Everything that can be automated should be automated."

H2O.ai, the open source leader in AI, today announced the latest additions to the speaker lineup for H2O AI World London, a two-day interactive event featuring deep-dive technical sessions, talks on real-world business use cases and hands-on training. With speakers from PwC, Barclays, NVIDIA, IBM, Citi and more, the conference will bring together data scientists, business analysts and executives across multiple industries to discuss the latest trends in artificial intelligence, machine learning and data science, important use cases and the biggest challenges currently facing the industry. Join H2O.ai in London to connect with the community and learn how to harness the full value of AI, ML, deep learning and data science from industry-recognized speakers and hands-on training sessions. Register here to secure your spot. On day one of the conference, sessions will focus on hands-on technical training for H2O.ai's groundbreaking products, H2O Driverless AI, H2O-3 and Sparkling Water, to empower data scientists and analysts of all levels to work on projects faster and more efficiently through automation and state-of-the-art computing power.

Working alongside robots will be part of a new university course aimed at students entering careers as carers, therapists and social workers. The new university programme is designed to help people get comfortable working with'social robots' that will be their colleagues in the future, researchers say. A recent survey found that almost 40 per cent of people are afraid that robots will steal their jobs. Earlier this year NHS officials announced that robots will carry out dementia care within 20 years. Working alongside robots will be part of a new university courses aimed at students entering careers as carers. Scientists from Sligo Institute of Technology in Ireland are testing a'Paro' robot seal that reacts to petting and conversation.

It's August here in Arizona, and despite the occasional monsoon thunderstorm (and accompanying dust storm), the heat is on! While we stay huddled in our air-conditioned homes, cars and offices, we decided to turn up the heat on some of this year's hottest SEO trends. And who better to talk to about the latest SEO happenings than our very own Brandon Alisoglu, Digital Current's newest SEO Strategist? Brandon gave us his perspective on some of the industry's leading topics and cutting-edge updates. SEOs and digital content creators have to think about how search engines, devices and humans will be accessing their content in the future (and today).

Do you have an idea that could make you South Africa's most successful fintech entrepreneur? Are you looking to acquire the skills to launch a data-driven fintech business? A new one-year data science and business skills programme aims to assist aspirant SA fintech entrepreneurs. In an announcement today, the Explore Data Science Academy (Edsa) and Rand Merchant Investments' (RMI) fintech division, AlphaCode, said their Explore 10X programme would assist 20 aspiring SA future fintech entrepreneurs. Successful candidates will go through an intensive six-month data science-training programme, where they will learn how to design a fast-growing business along with the core digital skills needed to build a fintech organisation.

This video tutorial is all about AI Permeation and its applications. Artificial Intelligence has not become an essential part of our day to day life. AI Permeation is one of the most trending technology in 2018. We have covered about this trending technology and its applications in this video tutorial. For latest technology update, keep visiting our Tech Blogs at https://msatechnosoft.in/blogs/

Ray Poynter will be presenting a paper titled'Problems in Identifying Causality in Observational Data'. This is a topic that NewMR will be exploring over the next year or so. In market research, there is a big shift taking place from questions to observations, which brings many advantages. However, there are some methodological problems and weaknesses with observational data that need to be addressed. This workshop is a one-day workshop spread over two days, with a social evening included.

Facebook may be willing to foot the bill. On Tuesday, Facebook and Udacity announced the PyTorch Scholarship Challenge, offering students the opportunity to learn how to build, train, and deploy deep learning models. PyTorch is an open source deep learning framework that is growing in popularity among AI researchers due to its ease of use, clean Pythonic API, and flexibility, Stuart Frye, Udacity's vice president of partnerships, wrote in a Tuesday blog post. With PyTorch 1.0, now available in preview release, developers can more easily move from exploration to product development with a single unified framework, Frye wrote. The scholarship program will offer students the chance to learn in-demand deep learning skills with PyTorch, as well as earn a full scholarship to Udacity's Deep Learning Nanodegree program, according to the post.

Meta-learning, or learning to learn, is the science of systematically observing how different machine learning approaches perform on a wide range of learning tasks, and then learning from this experience, or meta-data, to learn new tasks much faster than otherwise possible. Not only does this dramatically speed up and improve the design of machine learning pipelines or neural architectures, it also allows us to replace hand-engineered algorithms with novel approaches learned in a data-driven way. In this chapter, we provide an overview of the state of the art in this fascinating and continuously evolving field.