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by ERIC TASSONE, FARZAN ROHANI We were part of a team of data scientists in Search Infrastructure at Google that took on the task of developing robust and automatic large-scale time series forecasting for our organization. In this post, we recount how we approached the task, describing initial stakeholder needs, the business and engineering contexts in which the challenge arose, and theoretical and pragmatic choices we made to implement our solution.
Increasingly, women executives are being called upon to take the lead in shaping the critical business functions that are most necessary to ensuring business value from Big Data and analytics investments.
It is nearly impossible to talk about Big Data without making frequent reference to a broad ecosystem of computer code that has been made available for use and modification by the general public at no charge. History of open source In the early days of computing, computer code could be considered an idea or method, […]. The post Open Source: A primer for Big Data appeared first on DSI Analytics.
Business Intelligence (BI) pros continue to look for outside professional services. Forty-nine percent of decision makers say their firms are already engaging and/or expanding their engagements with outside data and analytic service providers, and another 22% plan to do so in the next 12 months. There are two main reasons for this sustained trend: The […].
AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.
Deeplearning is the buzz word right now. I was working on the course for deep learning by Jeremy Howard and one thing I noticed were pretrained deep Neural Networks. In the first lesson he used the pretrained NN to predict on the Dogs vs Cats competition on Kaggle to achieve very good results. What are pretrained Neural Networks? So let me tell you about the background a little bit.
We are thrilled to announce we have been awarded the Omega North Face Award for excellence in service delivery for the fourth year in a row. Our Net Promoter Score (NPS) – the gold standard for measuring customer loyalty – has a weighted average of 90 over these four years.
The problem for brands, of course, is that it’s no longer as easy to know where campaigns are appearing. There are literally millions of websites and apps. And some of them publish material that no brand would want its name associated with.
The problem for brands, of course, is that it’s no longer as easy to know where campaigns are appearing. There are literally millions of websites and apps. And some of them publish material that no brand would want its name associated with.
Newton once said that “God does not play dice with the universe” But actually he does. Everything happening around us could be explained in terms of probabilities. We repeatedly watch things around us happen due to chances, yet we never learn. We always get dumbfounded by the playfulness of nature. One of such ways intuition plays with us is with the Birthday problem.
Recently Quora put out a Question similarity competition on Kaggle. This is the first time I was attempting an NLP problem so a lot to learn. The one thing that blew my mind away was the word2vec embeddings. Till now whenever I heard the term word2vec I visualized it as a way to create a bag of words vector for a sentence.
Ever since Nutanix pioneered Hyper-Converged Infrastructure and made the case for the Enterprise Cloud, we’ve stood out from the competition. We differentiate ourselves with our superior product and exceptional product support, as shown by our continued streak of a 90+ Net Promoter Score (NPS).
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
As a forward-thinking Nutanix partner focused on delivering the best results for your customers, you might tend to be a bit of an overachiever at times.
Since launching.heart last September, we’ve rolled out a number of programs and initiatives that continue to emphasize our goals of giving back and encouraging gender diversity in tech.
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