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Machine Learning

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  • Reimagining the Contact Center with Bots & AI
    Reimagining the Contact Center with Bots & AI
    Abinash Tripathy, Co-founder, Helpshift Recorded: Dec 13 2018 62 mins
    Bots, artificial intelligence, and messaging — cost-effective, easy-to-implement automation technology —- is gaining a major foothold in customer service organizations, and the impact is palpable. Contact centers are on track to shrink by 50 percent in the next three years as routine tasks are taken over by faster, efficiency-saving bots that can triage requests, boost customer satisfaction, and offer an 8.6 percent increase in profit margin per customer.

    These technologies are also making it easy to tap into the gig economy, which is producing a growing supply of tech-savvy labor for companies that also saves costs. For workers, it means flexible arrangements with low barriers to entry, plus more satisfying employment, now that the grunt work has been eliminated by automation.

    AI and automation is set to level up the workforce, the economy, and your bottom line. For a closer look at the long-term implications of automation, how to invest in the brave new world of work, and more, don’t miss this VB Live event!

    Attend this webinar and learn:

    * The workforce implications of customer service bots
    * How bots and employees can work side-by-side
    * What smart companies are doing to lay the groundwork
    * Future of work - what does it look like?

    Speakers:

    * Abinash Tripathy, Co-founder, Helpshift
    * Peter Ryan, Principal Analyst, Ryan Strategic Advisory
    * Stewart Rogers, Analyst-at-Large, VentureBeat
    * Dilan Yuksel Moderator, VentureBeat

    Sponsored by Helpshift
  • Fight gaming fraud with AI and machine learning
    Fight gaming fraud with AI and machine learning
    Jeff Sakasegawa, Trust and Safety Architect, Sift Science Recorded: Jul 31 2018 61 mins
    Globally there are 2.2 billion active gamers, and 47 percent of them shell out cash while they play. And 100 percent of them are at risk from fraudsters who rip off everything from a gamer’s identity to their credit cards, online goods, and trust in your company. With every instance of fraud, your reputation takes a nose dive, driving away customers and directly impacting your bottom line.

    But fraud is notoriously difficult to combat. Legacy rules-based approaches have never been able to keep up with fraudsters, who constantly evolve their techniques using sophisticated technology like automated scripts and bots.

    That’s why machine learning and artificial intelligence are being leveraged to detect fraud before it affects your company and end users. Machine learning can sift through billions of game events and analyze vast streams of data in real time to stop fraud in its tracks.

    To learn more about how machine learning and AI can keep your game and players safe from increasingly aggressive online criminals, don’t miss this VB Live event!

    In this webinar, you'll learn:
    * How the gaming industry can secure gamer data and build trust
    * How account takeover, fake licensing, spam, and scams pose a particular challenge to gamers and gaming platforms
    * What policies your company should have in place around data breach ransom
    * How to combat trolling

    Speakers:
    * Jeff Sakasegawa, Trust and Safety Architect, Sift Science
    * Dean Takahashi, Lead Writer, GamesBeat
    * Scott Adams, CEO FraudPvP.com, Former Director of Fraud & Risk, Riot Games
    * Rachael Brownell, Moderator, VentureBeat

    Sponsored by Sift Science
  • Does it matter if an algorithm can't explain how it knows what it knows?
    Does it matter if an algorithm can't explain how it knows what it knows?
    Beau Walker, Founder, Method Data Science Recorded: May 24 2018 34 mins
    With the General Data Protection Regulation (GDPR) becoming enforceable in the EU on May 25, 2018, many data scientists are worried about the impact that this regulation and similar initiatives in other countries that give consumers a "right to explanation" of decisions made by algorithms will have on the field of predictive and prescriptive analytics.

    In this session, Beau will discuss the role of interpretable algorithms in data science as well as explore tools and methods for explaining high-performing algorithms.

    Beau Walker has a Juris Doctorate (law degree) and BS and MS Degrees in Biology and Ecology and Evolution. Beau has worked in many domains including academia, pharma, healthcare, life sciences, insurance, legal, financial services, marketing, and IoT.
  • Semantic AI: Bringing Machine Learning and Knowledge Graphs Together
    Semantic AI: Bringing Machine Learning and Knowledge Graphs Together
    Kirk Borne, Principal Data Scientist, Booz Allen Hamilton & Andreas Blumauer, CEO, Managing Partner Semantic Web Company Recorded: May 23 2018 64 mins
    Implementing AI applications based on machine learning is a significant topic for organizations embracing digital transformation. By 2020, 30% of CIOs will include AI in their top five investment priorities according to Gartner’s Top 10 Strategic Technology Trends for 2018: Intelligent Apps and Analytics. But to deliver on the AI promise, organizations need to generate good quality data to train the algorithms. Failure to do so will result in the following scenario: "When you automate a mess, you get an automated mess."

    This webinar covers:

    - An introduction to machine learning use cases and challenges provided by Kirk Borne, Principal Data Scientist at Booz Allen Hamilton and top data science and big data influencer.
    - How to achieve good data quality based on harmonized semantic metadata presented by Andreas Blumauer, CEO and co-founder of Semantic Web Company and a pioneer in the application of semantic web standards for enterprise data integration.
    - How to apply a combined approach when semantic knowledge models and machine learning build the basis of your cognitive computing. (See Attachment: The Knowledge Graph as the Default Data Model for Machine Learning)
    - Why a combination of machine and human computation approaches is required, not only from an ethical but also from a technical perspective.
  • How AI is Changing Marketing
    How AI is Changing Marketing
    Gil Allouche, CEO, Metadata.io Recorded: May 17 2018 43 mins
    In this webinar, Metadata.io CEO Gil Allouche will talk about the different ways AI is being used by marketers. From analyzing data to orchestrating new marketing campaigns, AI is powering marketing activities in new and exciting ways and affecting interactions throughout the entire customer lifecycle. As an example of how AI can have a tremendous impact on marketing practices, Gil will focus on its role in lead generation. Webinar attendees will learn:

    - What Machine Learning is in relation to AI and how it connects your data to find patterns
    - Examples of how machine learning can identify target audiences, including the 20 percent that creates 80 percent of your revenue
    - How AI technology can help marketers prioritize their budgets to focus on the most effective programs
    - Starting with small, iterative uses of AI in marketing can be the most effective way to understand what will yield the most ROI

    Gil Allouche founded Metadata.io to make demand generation easy for non-technical marketers. The Metadata.io platform and AI Operator evolved from Gil's experiences hacking various marketing and CRM systems to get the solutions he needed.
  • Customer-Centered AI: A Radical Strategy
    Customer-Centered AI: A Radical Strategy
    Geordie Kaytes, Partner, Heroic Recorded: May 16 2018 34 mins
    AI is a powerful tool, but often companies get more excited about their technology than in the customer value they’re creating. Geordie Kaytes will share a framework for building customer-centered AI products. You’ll learn how to craft a far-reaching vision and strategy centered around customer needs and balance that vision with the day-to-day needs of your company.

    Learn a framework for creating and communicating a vision that describes the overall direction of your AI product, a defined product strategy, a cross-functional roadmap aligned with the strategy, and a list of metrics that track progress towards the strategy

    About the Speaker: Geordie Kaytes is the director of UX strategy for Boston-area UI/UX studio Fresh Tilled Soil and a partner at Heroic (https://www.heroicteam.com), a design leadership coaching firm that helps growing companies scale their digital product capabilities. A digital product design leader with deep experience in design process transformation and cross-functional expertise in design, strategy, and technology, Geordie has helped companies in a broad range of industries develop a 360-degree view of their product design processes. Previously, he did his obligatory tour of duty in management consulting. He holds a BA from Yale in political science. He is a coauthor of the Medium publication Radical Product.
  • Intelligent Agents and a New Class of Perceived Errors
    Intelligent Agents and a New Class of Perceived Errors
    Dennis R. Mortensen, CEO and Founder, x.ai Recorded: May 16 2018 47 mins
    As we move to the conversational UI and take advantage of NLP and AI in general, we change the way we interact with technology dramatically. The standard GUI is many times fully eliminated, leading to novel challenges in UX. Tasks are removed from the user’s oversight with invisible or seamless software, and the output is not always as expected. But sometimes that output is correct within the parameters given and simply perceived as an error.

    Dennis will talk through where x.ai has encountered error perception issues as we seek to develop frictionless software, how we thought about the problem and the communication strategies we’re exploring to resolve it.
  • Network Telemetry & Analytics in the Age of Big Data & AI
    Network Telemetry & Analytics in the Age of Big Data & AI
    Ruturaj Pathak, Senior Product Manager, Networking BU, Inventec Recorded: May 15 2018 35 mins
    We are seeing a sea change in networking. SDN has enabled improvements in network telemetry and analytics.

    In this presentation, I will talk about the current challenges that are out there and how the technology change is helping us to improve the overall network telemetry. Furthermore, I will share how deep learning techniques are being used in this field. Please join this webinar to understand how the field of network telemetry is changing.
  • The Predictive Bank of the Future: How AI will Change Banking Forever
    The Predictive Bank of the Future: How AI will Change Banking Forever
    Tariq Ali Asghar, CEO, Emerging Star investment Group Recorded: May 15 2018 47 mins
    This Webinar explains how Big Data, Artificial Intelligence, and Machine Learning is going to transform the future Banking Industry. Banks which can manage this Big Data evolution successfully will survive and thrive, and give a more holistic and personalized customer service, thereby increasing their revenues tremendously.

    The key takeaway from this Webinar is that “Right information at the right place and the right time is going to be the real money and will shape the future of Banking Industry.”

    Tariq is a Fintech Expert, writer, and thinker based in Toronto Canada and is currently working on an initiative to disrupt the conventional Banking Industry with “Big Data Predictive Analytics Model” of his startup.
  • An Introduction to Deep Learning
    An Introduction to Deep Learning
    Mustafa Kabul, Principal Data Scientist, SAS Recorded: May 15 2018 64 mins
    In this webinar, Mustafa Kabul, Principal Data Scientist, SAS, will provide an introduction to deep learning and its applications.

    Mustafa is a data scientist in the Artificial Intelligence and Machine Learning R&D at SAS, where he leads innovative projects for SAS’s next-generation AI-enabled analytics products, including applications of deep learning. His current focus is on applying deep reinforcement learning to operational problems in the CRM and IoT spaces. An operations research expert working at the interface of machine learning and optimization, previously, he developed distributed, large-scale integer optimization algorithms for marketing optimization problems. Ever the optimization enthusiast, Mustafa always looks into ways to improve the algorithms. Nowadays his favorites are the distributed stochastic gradient and online learning methods. Mustafa holds a PhD from the University of North Carolina at Chapel Hill, where his research focused on game theory models of supply chains selling to strategic customers.

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