With access to mountains of data -- scoured, analyzed, and made actionable thanks to Artificial Intelligence, machine learning, and neural networking -- enterprise organizations are staking their claim on seamless, context-aware customer interactions as a business differentiator. New authentication technologies in personalized digital self-service can help deliver security, fraud prevention, and have a demonstrable impact on an enterprise's bottom line. Indeed "zero-effort authentication" enables intelligent automation, reduced customer effort (no more PINs and passwords), reduced call handling time, and improved confidence in security. Enterprises are building zero-effort authentication strategies for maximum return on investment and increased customer loyalty. In this on-demand webinar, Ravin Sanjith (Intelligent Authentication, Opus Research) and Alexey Khitrov (CEO, ID R&D) will discuss how zero-effort authentication in voice-centric channels leverage AI and the latest advancements in speech processing and multi-modal biometrics.

Learn to carry out pre-processing, visualization and machine learning tasks such as: clustering, classification and regression in R. You will be able to mine insights from text data and Twitter to give yourself & your company a competitive edge. You'll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R. My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real life.

Artificial intelligence (AI) is the hottest topic currently out there - no doubt about that. Neural networks in particular have seen a lot of attention and they will be used everywhere -self driving cars, predictions in finance and sales forecasts - everywhere and across all industries. To be successful in the working world of tomorrow we have to expose ourselves to this interesting topic - and from my personal experience - coding your own neural network is the best way to understand how they work. "From my personal experience I can tell you that companies will actively searching for you if you aquire some skills in the data science field. Diving into this topic can not only immensly improve your career opportunities but also your job satisfaction!"

Write queries using little-known but powerful, SQL features implemented in Oracle's database engine. You will be able to take advantage of Oracle's power in implementing business logic, thereby maximizing return from your company's investment in Oracle Database products. Important features and aspects of SQL covered in this book include the model clause, row pattern matching, analytic and aggregate functions, and recursive subquery factoring, just to name a few. The focus is on implementing business logic in pure SQL, with a comparison of different approaches that can be used to write SELECT statements to return results that drive good decision making and competitive action in the marketplace. Oracle SQL Revealed book covers features that are often not well known, and sometimes not implemented in competing products.

As one of the key members on the Demand Intelligence team that is part of AI group, you'll take ownership of the design and implementation of Course Hero's consumer-facing search. The key objective of the AI Group is to build a Semantic Knowledge Graph at Course Hero in order to help personalize bespoke learning experiences for students and help educators create unique course content. The charter for the Demand Intelligence team is to focus on delivering value to students and educators by enabling search intelligence and demand-side data products. This team will be building a Semantic Search engine using NLP and ML driven search mechanisms for the long-tail distribution and consumption of our document corpus. This also includes building user cohorts, an inference engine to infer intent, behavior, usage, trends, and economic demand curves powering content discovery and recommendations, pricing, and other applied data science initiatives.

Make big bets: In our Oxford University Course on Data Science for IoT, Jakub Langr covers GANs. Jakub has one of the best books on GANs I have seen. When I had lunch with Jakub in London – he mentioned something interesting. Three years ago .. (that's an age in AI!) he saw the potential of GANs and decided to bet his career on it by reading every paper, article etc on GANs. Three years later – he has a book on GANs and due to it he teaches at Oxford on GANs.

These questions can make you think THRICE! Machine learning and data science are being looked as the drivers of the next industrial revolution happening in the world today. This also means that there are numerous exciting startups looking for data scientists. What could be a better start for your aspiring career! However, still, getting into these roles is not easy. You obviously need to get excited about the idea, team and the vision of the company. You might also find some real difficult techincal questions on your way. The set of questions asked depend on what does the startup do. Do they build ML products? You should always find this out prior to beginning your interview preparation. To help you prepare for your next interview, I've prepared a list of 40 plausible & tricky questions which are likely to come across your way in interviews. If you can answer and understand these question, rest assured, you will give a tough fight in your job interview. Note: A key to answer these questions is to have concrete practical understanding on ML and related statistical concepts. You can get that know-how in our course'Introduction to Data Science'!

A movie montage for modern artificial intelligence might show a computer playing millions of games of chess or Go against itself to learn how to win. Now, researchers are exploring how the reinforcement learning technique that helped DeepMind's AlphaZero conquer the chess and Go could tackle an even more complex task--training a robotic knee to help amputees walk smoothly. This new application of AI based on reinforcement learning--an automated version of classic trial-and-error--has shown promise in small clinical experiments involving one able-bodied person and one amputee whose leg was cut off above the knee. Normally, human technicians spend hours working with amputees to manually adjust robotic limbs to work well with each person's style of walking. By comparison, the reinforcement learning technique automatically tuned a robotic knee, enabling the prosthetic wearers to walk smoothly on level ground within 10 minutes.

Apple's new AirPods might have been accidentally confirmed – but its own iPhone update. The latest beta version of the iOS software appears to not only suggest that new versions of the wireless earphones are coming soon, but also what one of their main features might be. The leak comes from a hidden part of the iOS 12.2 update which is currently available for developers. Inside a pop-up that is not visible without digging around is a suggestion about how those nearphones might work. While a user is setting up the option to speak to the phone's digital assistant just by saying "Hey, Siri", the message suggests that people will be able to do so just by speaking into their AirPods, rather than into their phone.

For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on our GitHub repo.