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. 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 >
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 >
In this webinar you’ll learn why (and how) leading companies are moving their learning strategies from "push" to "pull" models, enhancing the employee experience while reinforcing standards for critical topics like safety and compliance. L&D leader Lauren Clarke of Delaware North will also share her organization’s content curation journey and how they successfully implemented a pull learning strategy.Read more >
Saba Summer School Series:
Taking a collaborative approach to learning can help you better connect, engage, and retain your workforce, while at the same allowing you to achieve greater ROI from your L&D investments. In this webinar, you’ll discover why learning is most effective when it’s collaborative and ways you can foster a culture of collaborative learning within your organization.
The human brain makes it look easy. What our eyes see, we decode immediately and effortlessly. But is it that simple? In truth, how we process images is staggeringly complex. Inspired in part by our remarkable neurons, deep learning is a fast-growing area in machine learning research that shows promising breakthroughs in speech, text and image recognition. It’s based on endowing a neural network with many hidden layers, enabling a computer to learn tasks, organize information and find patterns on its own.
Recently, SAS took on a classical problem in machine learning research, the MNIST database, a data set containing thousands of handwritten digit images. Learn how we did – and what it reveals about the future of deep learning.
There are two key elements for mastering the digital transformation in every company: Learning & People Development. Join us to understand how SAP Education’s multiple award-winning solution can help you on the digital journey by empowering and educating your employees, partners & customers
Join us live on Tuesday, October 18th for a 30-minute free webinar and discover how AVEVE was able to bring down project costs, reduce operational expenses and accelerate return on investments at reduced total cost of adoption.
In this 30 min webcast you will get an overview of how SAP Hybris enriches the digital transformation plus a detailed walk through of how you can get enabled. Join us to see how simple it is through our personalised learning maps.Read more >
Learn the way you live, Love the way you learn!
State of the art learning management system brought to you by SAP SuccessFactors
The opportunities are endless! In this session, you’ll hear how Artificial Intelligence and machine learning can be leveraged inside your organization.
These technologies are on the precipice of huge change and adoption, and will be major trends in technology over the next few years. Stay ahead of the curve and learn how you can start implementing and utilizing these options for IT automation, platform implementation, predictive analytics, and more.
Listen to our interview at Big Data LDN with Sean Owen, Director of Data Science at Cloudera.
Sean will talk about the deep learning framework its seamless deployment in Hadoop clusters. He will also discuss some detailed applications and use cases to further visualize this intersection.
In a hypercompetitive world, faster and better decisions and actions are critical. So, can your individual staff members working in different functions find the right information at the right time to make that happen? Enterprise search systems can save as much as 30%* of the time spent by employees searching for information. The cumulative impact across the organization could be far-reaching. Come and find out how machine learning can accelerate intelligent search and knowledge discovery.
*Transparency Market Research
Do we base our approach to learning on past practice or expectations of future practice? Perhaps we think our past practices are 'best' and will not change much in the next 5-10 years?
6 years ago there wasn’t an iPad - and 10 years ago there were no iPhones. As the world changes so too must the practice of BC.
The needs of the generations that entered the workforce in the past 10 years will have to guide the nature of future practice - and that practice will need to inform what and how we learn.
This interactive session will examine generational change in the workplace, and the opportunity it presents to shape future practice.
Already strategic partners, Pivotal Software and Hortonworks deepened their relationship in Spring 2016 with the goal of providing enterprises the most complete modern data platform for advanced analytics and machine learning. As part of the expanded relationship, Hortonworks has introduced Hortonworks HDB, the market’s leading Hadoop Native SQL database and big data SQL machine learning engine based on Apache HAWQ and Apache MADlib (incubating).
Join Pivotal’s Jeff Kelly and Hortonworks’ Ian Fyfe in this webinar to learn more about:
• Advantages of Hortonworks HDB
• How it works
• When to consider HDB vs. Apache Hive
• HDB industry use cases
One of the main benefits of Machine Learning is being able to analyse a large amount of data at the speed and efficiency that would require a huge team of humans. This is something that has proven to be very necessary in the Financial Services industry, where insurance companies, banks, and lenders need actionable insights quickly.
Join this panel where we will discuss:
-Why is Machine Learning such a hot topic? What are the benefits/challenges?
-What is needed to do Machine Learning right?
-Case studies of how Machine Learning is helping financial institutions — better customer experience, faster actionable insights
-How ML is able to spot trends and patterns to mitigate risk