Amazon's Alexa assistant recently learned to speak new languages globally: Hindi, U.S. Spanish, and Brazilian Portuguese. Synthetic data aided substantially in this, explained Amazon senior manager for research science Janet Slifka in a post on the Alexa blog this morning, but it wasn't the end-all-be-all solution. They required new bootstrapping tools. One of the tools in question was developed by Amazon's Alexa AI Applied Modeling and Data Science group, and it uses a technique called grammar induction to analyze so-called golden utterances (i.e., canonical examples of customer requests proposed by Alexa feature teams) and produce a series of expressions that can generate similar sentences. The other -- guided resampling -- creates novel sentences by recombining words and phrases from examples in the available data, with an emphasis on optimizing the volume and distribution of the sentence types.

Autumn is as good a season to learn natural language processing as any other, and why not do so with quality, free online courses? This is a collection of just such free, quality online NLP courses, from such esteemed institutions of learning as Stanford, Oxford, University of Washington, and UC Berkeley. There are also offerings from independent sources like Yandex Data School, and even a short practical course on spaCy by one of its creators and co-founder of the company which steers its development. So whether you are looking for theoretical or practical, or are a beginner or an advanced learner, the content included herein won't fail on living up to the promise of being 10 free top notch natural language processing courses. So dig in and learn NLP today.

Conversational interfaces have gone mainstream. The technology behind keeps crossing new milestones, the result of which chatbots have transformed from simple Q&A systems to intelligent personal assistants. As a result, bots found widespread application in diverse areas, most recently in education. Although education stayed backward in terms of technology adoption, lately it took on a renewed quest to incorporate it. Educators are on the lookout for innovative ed-tech systems for efficient tutoring and students increasingly prefer personalized learning environments.

Editor's Note: In today's fast-paced news cycle, we know it's difficult to keep up with the latest and greatest HR trends and stories. To make sure you're updated, we're recapping the most popular trends, events and conversations every month in our "In Case You Missed It" series. Each year, the HR Tech Conference gathers HR experts and professionals to discuss how companies can use technology to drive more successful programs and improve the talent experience. At this year's conference, speakers placed more focus on artificial intelligence, machine learning and data analytics, and how these emerging technologies can optimize HR, recruiting and diversity programs. The conference also touched upon more recent trends like virtual reality and revealed how this technology can be used to train and engage today's workforce. In case you missed it, we've compiled the top trends from HR Tech.

This live classroom course is new for 2018! It focuses on the newest technologies of Microsoft Machine Learning Server and SQL Server 2017. This 2-day course introduces the most important concepts and Tools, and should be followed by the 3-day course: Intermediate Machine Learning in R on SQL Server and Microsoft ML Server. If you have attended a prior course on Machine Learning, like Rafals week-long class Practical Data Science course offered in 2015-2017, and if you are versed in model validity, accuracy, and reliability, then you should consider attending the Intermediate course only. Ask yourself these questions: Can I explain the difference between cross-validation and hold-out testing?

TORONTO, Thursday, Oct. 10, 2019 - Docebo Inc. (TSX:DCBO) ("Docebo" or the "Company"), has successfully launched its IPO on the Toronto Stock Exchange, marking a milestone moment and a significant achievement for the SaaS e-Learning platform. Docebo, developer of a leading AI-powered learning platform, has seen significant growth thanks to its dedication to its customers' success and consistent string of innovation, from launching its social learning functionality in 2016 to the implementation of in-house build learning specific artificial intelligence algorithms in 2018. Docebo has since become a truly international company with offices in Toronto, Milan, London, Atlanta, and Dubai. With over 2/3s of its revenue based in North America, Docebo's headquarters in Canada has been the hub for the company's international expansion and growth. "Completing this IPO is an exciting achievement for the organization and comes as a result of the talent and dedication of our team and support from our global base of customers and partners," said Claudio Erba, CEO of Docebo.

Data Science is such a broad field that includes several subdivisions like data preparation and exploration; data representation and transformation; data visualization and presentation; predictive analytics; machine learning, etc. For beginners, learning the fundamentals of data science can be a very daunting task especially if you don't have proper guidance as to the necessary training required, or what courses to take, and in what order. Before discussing the steps necessary to become a data scientist, let's discuss the skills that every data scientist should have in his skills set toolbox. I started learning data science about a year ago. It was quite challenging from the beginning, but let me share with you the approach that worked for me.

The government has unveiled plans to invest £13m in postgraduate conversion courses in data science and artificial intelligence. The initiative will see universities and higher education providers partner with industry to develop new courses that train graduates, who may have studied a non-STEM degree, in the skills required to take up jobs in the field. The funding forms part of a wider £400m investment in maths, digital and technical education through the government's AI sector deal, which was launched last year amid criticism that ministers were failing to protect the UK's tech scene ahead of Brexit. Under the new initiative, the Office for Students and the Department for Digital, Culture, Media and Sport have allocated £3m to course development and £10m to scholarships for candidates from underrepresented backgrounds, including female, disabled and black students. It is hoped that 2,500 students will have enrolled in one of the new courses by 2023.

Despite becoming an increasingly common phrase, there is still some confusion around machine learning (ML) and how it relates to artificial intelligence (AI). Key to machine learning is data; algorithms are designed to learn from this data and then make a determination or prediction about the subject. In machine learning, computers don't have to be programmed to complete tasks, it's about getting them to actually acquire knowledge. Machine learning is a subset of the much broader world of artificial intelligence, however, AI is more focused on developing a machine that can do something that only a human would normally be able to do. In the field of education, there are many opportunities for machine learning to make an impact. However, there are also concerns that need to be addressed, not least the vast amounts of data that have to be stored and analysed in order to create effective machine learning algorithms.

Meet DigiDoug, the first digital human to give a TED talk in real time. DigiDoug is the virtual version of Dr. Doug Roble, senior director of Software R&D at Digital Domain, the award-winning visual effects studio behind the characters and visual effects for movies like The Curious Case of Benjamin Button, Maleficent, Disney's The Beauty and the Beast and Avengers: Endgame. Roble and Digital Domain's Digital Human Group have presented DigiDoug at multiple events, showcasing their state-of-the-art digital human technology that's driven by an inertial motion-capture suit and a single camera capture for facial animation. But to capture and recreate emotions and actions in real time, the Los Angeles-based studio turned to more powerful and advanced technology: machine learning and real-time rendering. With NVIDIA RTX technology and Unreal Engine from Epic Games, Digital Domain is bringing photorealistic digital humans to life -- all in real time.