Analytics Vidhya
MAY 11, 2020
A Simple Analogy to Explain Decision Tree vs. Random Forest Let’s start with a thought experiment that will illustrate the difference between a decision. The post Decision Tree vs. Random Forest – Which Algorithm Should you Use? appeared first on Analytics Vidhya.
Corinium
MAY 11, 2020
HPE Global Field CTO Matt Maccaux explored why so many enterprises struggle to operationalize AI in his 2020 Data Champions Online US keynote presentation. Why Enterprises Struggle to Industrialize AI. Industrialization is the process of expanding the application of a technology so that a business can benefit from it at scale.
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Juice Analytics
MAY 11, 2020
Dresner Advisory Services’ report about self-service business intelligence uncovered a surprising result. Among all the technologies and initiatives that respondents consider important, the item that topped the list was reporting. [link]. Let that sink in. Among all the hot analytics initiatives to choose from (big data, IoT, NLP, data storytelling, cognitive BI, GDPR), plain old reporting is what is considered the most important strategic initiative.
Corinium
MAY 11, 2020
In episode 4 Abboud shares how coffee takes him on a journey, his passion for analytics & the need to bring humanity to leadership during a crisis. Every now and then you meet someone you just gel with. Abboud is one of those people for me. We've been working together in the data analytics community across the Middle East & Africa for the past 3 years and have formed a strong friendship over that time.
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
Dataiku
MAY 11, 2020
Arguably more famous today than Michael Bay’s Transformers (at least among the deep learning community), NLP transformer architecture and transformer-based models have been breaking all kinds of performance records across an array of NLP tasks.
Corinium
MAY 11, 2020
This is episode 3 of Data Conversations Over Coffee and we're speaking to Ben Jones.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
bridgei2i
MAY 11, 2020
Catalysing Digital CX using Data Science Capabilities in the Post COVID World. As COVID-19 disrupts business operations across the globe, the Customer Experience(CX) teams in several organizations are feeling the impact. With operations shifting to remote locations for both employees and clients, everyone is looking at a change in the operating models.
Paris Technologies
MAY 11, 2020
How does financial modeling in PowerExcel compare to Excel? Here are some concrete examples that will show how PowerExcel can improve productivity and collaboration in finance teams.
Teradata
MAY 11, 2020
Learn how advanced analytics are being used in China amidst the COVID-19 pandemic to help combat the spread of coronavirus now and in the future.
Andrew White
MAY 11, 2020
I was reading a paper over the weekend that explored the relationship between financial frictions and productivity. This does not sound like a barnstormer, I admit, but stick with me for a few minutes. This does get interesting. It turns out that CDOs, looking to exploit AI, data and analytics to drive productivity need to work with CFO’s who are looking at their firm’s debts.
Speaker: Anne Steiner and David Laribee
As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.
Nutanix
MAY 11, 2020
Extra! Extra! Read all about it! Issue 7 of NEXT Magazine is here, and is overflowing with can’t-miss content.
Jet Global
MAY 11, 2020
The COVID-19 crisis has changed the way we work. Now more than ever, finance and accounting workers around the world are discovering the merits and the pitfalls of working remotely. This also presents a fresh opportunity for finance and accounting managers to consider how their teams operate. As companies have scrambled to deploy online meeting platforms and offer collaboration tools, many are asking whether there might be other technology tools available that could help their employees to work
Nutanix
MAY 11, 2020
Extra! Extra! Read all about it! Issue 7 of NEXT Magazine is here, and is overflowing with can’t-miss content.
FineReport
MAY 11, 2020
What’s Wrong with Excel ?. In our daily work, which involves tables, charts, data analysis, and data processing, Excel must be our first choice. But when it comes to some more complicated data processing work, you need VBA to help, and it often takes a lot of time to learn VBA well. And when the amount of data becomes larger, Excel’s processing efficiency will become very low.
Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage
Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.
Nutanix
MAY 11, 2020
Extra! Extra! Read all about it! Issue 7 of NEXT Magazine is here, and is overflowing with can’t-miss content.
Octopai
MAY 11, 2020
Data literacy has been gaining traction inside the business intelligence (BI) and operations communities for a couple of years. Despite its importance, a Data Literacy Project report found only 24% of the global workforce would describe themselves as “data literate.”. This low number indicates it’s difficult to achieve data literacy. The concept has not been easy for the greater business community to grasp.
O'Reilly on Data
MAY 11, 2020
You probably interact with fifty to a hundred machine learning products every day, from your social media feeds and YouTube recommendations to your email spam filter and the updates that the New York Times, CNN, or Fox News decide to push, not to mention the hidden models that place ads on the websites you visit, and that redesign your ‘experience’ on the fly.
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