Machine learning and artificial intelligence enable customers to learn from data without being explicitly programmed. This changes hundreds of applications in the enterprises as machines can now work with unstructured data like natural language, text, images and videos. Machine Learning enables enterprises to re-imagine business processes with digital intelligence. Learn how you can realize the intelligent enterprise for your business.
In this webinar, speaker and Big Data influencer Ronald van Loon and Dr. Markus Noga, Vice President Machine Learning, Innovation Center Network, SAP SE will discuss the following:
•What is machine learning and artificial intelligence?
•Why is machine learning advancing so rapidly?
•Benefits of machine learning
•Machine learning use cases
•Machine Learning technology and apps
•How to get started?
As video becomes more popular, more accessible to create, and more in demand from customers and stakeholders, it's important to learn how to start creating video. Video doesn't have to be complicated, and you don't have to become a video professional to make effective and engaging video. Learning a few of the essentials will put you on your way to make great videos.
Join me, Scott Abel, The Content Wrangler, and my special guest, Matthew Pierce, Learning & Video Ambassador at TechSmith for this presentation. Matt will prepare you to get started with video with practical tips and steps. He will address the entire lifecycle from preproduction through distribution, and points in between to help you get with started creating videos.
What are the keys actions and components to getting started with video.
Shooting and editing tips, tricks and techniques.
Producing and distribution — what you need to be successful
ABOUT MATTHEW PIERCE
Matthew Pierce, Learning & Video Ambassador for TechSmith Corporation, is an advocate for using video for learning, marking, and communicating. Throughout Matthew's career, he has managed training, instructional design, support, public relations, social media, and video teams at TechSmith. He has also been an instructional designer. Matt regularly contributes to several online publications in the US and UK. He has an MS in instructional technology from Indiana University.
Machine learning is changing the way organizations look at analytics. Data scientists are being recognized as a key component in organizational analytics, but management often doesn't understand their work or know how to effectively manage them.
Many businesses understand that analytics has moved beyond the data warehouse, and are pushing analysts and IT to grab and analyze data from new sources, even though they may not be ready to derive business value from it.
Open source is seen as the path to machine learning innovation, despite challenges with deployment and approachable user interfaces. For organizations using or looking to adopt machine learning techniques, moving forward may be a challenge and measuring success even trickier.
In this webcast, we will:
-Discuss how different organizations are finding success with machine learning.
-Look at how organizations are feeding the creativity of data scientists, making analytics accessible to business experts, and pushing the analytics closer to the data.
-Identify how organizations are automating analytics processes in order to free up time for new analytics, new data and new business problem domains, ultimately creating real competitive advantage.
The rise of social learning has created a new landscape for L&D professionals to explore. This webinar will examine the foundations of Social Learning and discuss how our learners are able to adapt and thrive in this space - mastering the technology and understanding the facets of Social Leadership and ways we engage as part of online communities.Read more >
In this webinar we discuss various DL applications and the optimized Intel DL environment including hardware, software, and tools. Ravi and Andres will explain the difficulty in scale training across multiple nodes and what Intel is doing to improve scaling efficiency. Various hyperparameters use to train DL networks are explain with a particular focus on Caffe.Read more >
A key task to create appropriate analytic models in machine learning or deep learning is the integration and preparation of data sets from various sources like files, databases, big data storages, sensors or social networks. This step can take up to 50% of the whole project.
This session compares different alternative techniques to prepare data, including extract-transform-load (ETL) batch processing, streaming analytics ingestion, and data wrangling within visual analytics. Various options and their trade-offs are shown in live demos using different advanced analytics technologies and open source frameworks such as R, Python, Apache Spark, Talend or KNIME. The session also discusses how this is related to visual analytics, and best practices for how the data scientist and business user should work together to build good analytic models.
Key takeaways for the audience:
- Learn various option for preparing data sets to build analytic models
- Understand the pros and cons and the targeted persona for each option
- See different technologies and open source frameworks for data preparation
- Understand the relation to visual analytics and streaming analytics, and how these concepts are actually leveraged to build the analytic model after data preparation
Deep neural networks have been used successfully in domains like speech recognition, computer vision, and natural language processing. Deploying a successful deep-learning solution requires high-performance computational power to efficiently process vast amounts of data. This webinar will share insights on the effectiveness of different neural network architectures and algorithms.Read more >
It’s easy to get caught in the excitement of machine learning and start optimizing RMSE, AUC or recall, but machine learning success starts with aligning to the business.
Join Patrick Rice, CEO of Lumidatum, as he leverages his decade of experience in big data analytics including implementing machine learning solutions at Amazon to outline the secrets to winning at machine learning and delivering real ROI to the business.
Reinforcement Learning (RL) is a field within AI that makes machines learn by trial-and-error. RL systems have improved enormously in the recent years, being able to master games like Space Invaders or Go.
However, we have many challenges ahead: How can we make RL systems that live in the real world, with real people? How can we make sure these systems remain stable and well-behaved?
In this talk we will explore these challenges and suggest a few ways forward to bring useful RL technology to people's daily lives.
There is a misconception that infusing automation into the customer experience will make it less human, and thus less relatable, to consumers. On the contrary, companies are pioneering AI technologies to enable them to gain a deeper understanding of the people they serve, resulting in experiences that are more relevant, personal, emotional, and ultimately rewarding--for customer and company alike.
Join Assaf Baciu, head of product and co-founder of Persado, who will demonstrate how Fortune 1000 brands are leveraging machine learning to create emotional relationships with their audiences.
Machine learning is all about the data, but it's often out of reach for analytics teams working at scale. Cloudera customers such as Wargaming.net can store, process and analyse 550 million events each day to help them improve gamers’ experiences and increase their customer lifetime value.
Whether you are new to machine learning and advanced analytics, or you already take advantage of the possibilities, this session will explore practical examples and give you some new ideas to take away. Discover how enterprise organisations can accelerate machine learning from exploration to production by empowering their data scientists with R, Python, Spark and more in one unified platform.
Good applications of machine learning and AI can be difficult to pull off. Join Brian Lange, Partner and Data Scientist at data science firm Datascope, as he discusses a variety of ways machine learning and AI can fail (from technical to human factors) so that you can avoid repeating them yourself.Read more >
Machine Learning, Artificial Intelligence and Natural Language Processing (NLP) are transforming the technological landscape in a wide range of applications. How Machine Learning frameworks have been applied in the real world continues to evolve and affect our daily lives, especially with chat bots.
In this session Dr. Hodeghatta Rao will explain the fundamental concepts of Natural Language Processing (NLP), what are the practical applications of NLP, how machine learning is adopted to process the natural language and finally end with an overview of QnA (chat) system.
Last year, marketers were focused on predictive analytics and ABM. This year is proving to be all about how machine learning and artificial intelligence will impact marketing strategies.
Leading organisations powering the marketing technology landscape are quickly innovating to introduce new technologies and are determined to make marketers successful. But just how will this happen? What questions should you be asking in order to innovate on your go-to-market plans?
Join us on Tuesday 4th April as we discuss how machine learning and artificial intelligence is shaping marketing decisions, driving growth and improving the customer experience.
As businesses begin to rely more on data-driven Artificial Intelligence applications, the new applications lead to new business issues, security, and privacy concerns. Each bank also needs to have a transparent system for total audit-ability so one can see who did what, and when. Bank can use AI Deep Learning techniques to identify erroneous or incomplete data to avoid misleading decisions.The new AI applications introduce a number of business, security and privacy issues which will have to be addressed. Neural Network, Natural Language Processing, Image Recognition, Speech Recognition and Sentimental Analysis techniques are Deep Learning techniques used in Banks and Financial Services. AI Deep Learning techniques are used to help with anti-money laundering programs, know-your-customer checks, sanctions list monitoring, billing fraud oversight or other general compliance functions, artificial intelligence can:
- Improve efficiency
- Weed out false-positive results
- Reduce costs and increase profits.
- Make better use of workers’ time and company resources
- Help banks handle their compliance monitoring
- Automate some legal and regulatory work
- Handle most customer service and improve customer experience
- Help in detection of Fraud
- Creates a massive competitive advantage
Bhagvan Kommadi, Founder, Architect Corner has around 20 years experience spanning in the creation of products & incubation of Product Startups. He has done Masters in Industrial Systems Engineering at Georgia Institute of Technology (1997) and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras (1993).Architect Corner is in CIO Advisor Top 25 Fast Growing AI startups in APAC for 2017. Architect Corner is part of Citi T4I Growth Accelerator.
In this webinar, Dr. Griffin Fernandez from The Educe Group will share best practices for implementing and driving adoption of learning management systems within colleges and universities. You’ll also hear from campus leaders at two top universities as they share their experience with implementing learning management systems. Sondra Hornsey, HIPAA Privacy Officer at Washington University in St. Louis, will discuss the human resources training requirements that drove the institution’s decision to implement Saba Cloud, while Dr. Michael Blayney, Executive Director of Research Safety at Northwestern University, will focus more narrowly on the unique requirements associated with university research compliance. Each will discuss the challenges that led them to seek out a learning management system, the planning and vendor evaluation processes, and how they have implemented Saba Cloud to achieve institutional goals and improve university business processes.Read more >