This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Ariel Weintraub on Putting Data to Work in the SOC and IAM Ariel Weintraub joined MassMutual last fall to focus on putting datascience to work to help improve the insurance company's security operations and identity and access management programs. What are the early use cases and lessons learned?
CEO Martin Roesch Says Netography Can Detect Anomalous Behavior Without Human Help Netography has added more detection features and datascience capabilities to help large enterprises better understand what's on their networks, according to CEO Martin Roesch.
Cyentia Institute Partner Wade Baker Shares Insights on Analyzing Ransomware Data Unlocking the data generated by ransomware attacks is helping organizations better understand the risks, adopt defensive technologies and prepare for future attacks, says Wade Baker, partner at Cyentia Institute.
A notable exception is OpenText™ Magellan™ and our DataScience projects. In these cases, customers can expect an approach which simply adds refinement iterations to the build phase or … The post An agile approach to DataScience appeared first on OpenText Blogs.
Greg Loughnane and Chris Alexiuk in this exciting webinar to learn all about: How to design and implement production-ready systems with guardrails, active monitoring of key evaluation metrics beyond latency and token count, managing prompts, and understanding the process for continuous improvement Best practices for setting up the proper mix of open- (..)
IBM DataScience and AI Elite team members Mehrnoosh Vahdat and Rachael Dottle were just one month into their IBM careers when they received their first assignment last July. . The project jettisoned them into the heart of Africa, where their banking client was looking to surface new business opportunities across the subcontinent.
How has the newer datascience technology such as Watson Studio, Watson Machine Learning and Watson OpenScale been picked up by the business partner community? I mentioned in our previous blog that I was pleasantly surprised at how many IBM Business Partners have established a DataScience practice.
Learn how the IBM Integrated Analytics System, a unified data platform built on the IBM Common SQL Engine, helps do datascience faster with high performance, embedded machine learning capabilities and built-in tools for data scientists to deliver analytics critical to increasing your organization’s competitiveness.
“The NITEC innovation challenge,” said Mike Street, Head of innovation and datascience at the NCI Agency, “is a great way for a wide range of companies and organizations to share their innovative products and services with the NCI Agency.
New Head of Enterprise Cybersecurity Succeeds CISO Jim Routh Less than a year ago, Ariel Weintraub was dabbling in datascience as head of security operations and engineering at MassMutual, working under CISO Jim Routh. Now she’s replaced Routh as the new head of enterprise cybersecurity - and she welcomes the challenge.
Many of the startups attempting to tackle this vexing problem are offering the promise of datascience and machine learning to automate the process of managing identities, although none of them even have the data collected to prove the accuracy and robustness of their proposed solutions. Leveraging datascience.
Though you may encounter the terms “datascience” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.
The datascience market is evolving rapidly. Many data scientists and developers today want to make use of the latest open source innovations during these steps. Many data scientists and developers today want to make use of the latest open source innovations during these steps.
INE’s suite of learning paths offers an incomparable depth of expertise across cybersecurity, cloud, networking, and datascience. INE Security is committed to delivering advanced technical training while also lowering the barriers worldwide for those looking to enter and excel in a cybersecurity career.
Today’s datascience and analytics teams are often composed of individuals with a variety of skill sets, educational backgrounds, levels of exposure to open source tools and professional needs. Here’s a typical breakdown:
Datascience was one of the hot topics of 2018, and it’s likely to dominate again in 2019. We've asked five key datascience influencers to take a look back at 2018 and look ahead at what's to come in 2019.
Organizations everywhere, from massive governments to the smallest start-ups, are in a race for the best-possible data expertise and tools. To help your team understand the datascience journey, IBM created the DataScience for All webcast.
As a result, data scientists can be liberated to commit more time to designing, testing and deploying machine learning models. To learn more about what these developments mean for the datascience community, I sat down with IBM’s Vice President of AI, IBM Research, to get his perspective.
It’s the next datascience gold rush! The post MicroServices: Today’s datascience gold rush appeared first on Data Security Blog | Thales eSecurity. Microservices is a very high-end, enabling technology to get teams to their goal quickly. And it’s happening. You could definitely feel the buzz at KubeCon.
RapidMiner, TIBCO Software, SAS and KNIME are among the leading providers of datascience and machine learning products, according to the latest Gartner Magic Quadrant report.
If you’re a data scientist or leading a team, Think 2019 is where you’ll want to be in February to hear success stories from clients using IBM’s datascience portfolio of solutions.
Recently, I sat down with Kyle Weeks, Program Director for Ecosystems in DataScience and AI. I wanted to review some exciting new opportunities made possible by several recent developments in IBM DataScience:
Taking an agile approach to datascience helps deal with rapidly changing environments, uncertainty, complex solutions, emerging technologies, and ambiguous requirements inherent in these projects.
Predictive modeling and analytics have long been the domain of the data scientist and only the data scientist. But with modern tools, datascience is becoming a team sport—business analysts and subject matter experts can join the analysis.
In this Q&A, IBM financial services solution architect Irina Saburova discusses an insurance use case with IBM DataScience Marketing Lead Rosie Pongracz.
Starting from applying intelligent datascience where it matters most and progressively using it in every aspect of the business. The business that gets there first won’t necessarily win digital and AI game. It will be the one that ingrains digital and AI in its business as much as possible.
Machine learning has the potential to make the lives of marketers easier, but few marketing teams currently have the in-house datascience skills they need to take advantage of it.
The post University of Michigan “DataScience Ethics” 4-Week Course Offered for Free via Coursera appeared first on IG GURU. This course is offered for free on Coursera.
And now, early adopters of security data lakes like Snowflake are saving more than two-thirds of what they were paying for their Splunk license. The Cisco acquisition shall exacerbate these challenges and speed up the adoption of security data lakes.
John Thomas, IBM distinguished engineer and director of analytics, talks with Dave Vellante in NYC ahead of the recent “Change the Game: Winning with AI event in NYC” to talk about how the IBM DataScience Elite team offers datascience expertise as a service to a variety of clients to a variety of organizations, cutting across multiple industries. (..)
“Investigations of this kind are primarily conducted by Binance’s internal risk intelligence unit known as Binance Sentry as well as an analytics arm, the Security DataScience division.”
While datascience and machine learning are related, they are very different fields. In a nutshell, datascience brings structure to big data while machine learning focuses on learning from the data itself. What is datascience? This post will dive deeper into the nuances of each field.
Her path to datascience elite status is what makes her a valuable and unique practitioner for IBM clients. Learn more about Brittany Bogle in our new series profiling the technical experts helping clients reach their AI and machine learning goals.
When CyberTown, USA is fully built out, it’s backers envision it emerging as the world’s premier technology hub for cybersecurity and datascience. It’s mission has been to seek out and assist government cyber specialists in a position to enter the private sector and build commercial cyber and datascience companies.
via Beyond Unicorns: Educating, Classifying, and Certifying Business Data Scientists · Harvard DataScience Review Abstract There is increasing recognition that the data scientist ‘unicorn’—one who can master all the necessary skills of datascience required by businesses—exists only rarely, if at all.
“Based on several days of initial investigation by security, engineering, and datascience (and friends!), we have no evidence to suggest that any of your non-public data has been accessed, or that Reddit’s information has been published or distributed online.” ” continues the notice.
Cloud tagging, the process of labeling cloud assets by certain attributes or operational values, can unlock behavioral insights to optimize and automate cyber asset management at scale.
We organize all of the trending information in your field so you don't have to. Join 55,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content