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 >
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.
No matter how well your enterprise software solution has been configured and installed, the ultimate responsibility for delivering value lies with the people who use it. Learning & People Development are the two key elements for mastering the digital transformation in every company!
Join us live on November 15th for a 45-minute free webinar & demo to understand how SAP Education can help you on the digital journey by empowering and educating your employees and discover our new starter pack that will get you up and running in a few days!
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 >
Los avances de inteligencia artificial siguen aumentando y estos avances nos están llevando a un desarrollo impresionante y peligroso en la tecnología de ciberataques, los cuales causan que las amenazas sean más rápidas y más sofisticadas. Desde el ransomware inteligente hasta malware sofisticadas y personalizadas que se integran a la red, los equipos de seguridad están luchando para seguir el ritmo de la nueva generación de amenazas.
Dentro de la carrera de ciberarmas, una nueva estrategia es esencial para identificar y responder a los ataques de IA y a otros adversarios sutiles y avanzados. Durante el webinar, el Gerente Regional de Darktrace, Neil Goldfarb, y el Gerente Regional de CastInfo, Victor Ibañez, examinarán este desafío y explicarán por qué la ‘tecnología del sistema inmune’, propulsada por machine learning no-supervisado, será crítica en el futuro de la ciberdefensa.
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