datapine
APRIL 16, 2019
We read about it everywhere. The term ‘big data’ alone has become something of a buzzword in recent times – and for good reason. By leveraging the wealth of digital insights available at your fingertips and embracing the power of business intelligence , it’s possible to make more informed decisions that will lead to commercial growth, evolution, and an increased bottom line.
O'Reilly on Data
APRIL 9, 2019
Or, why science and engineering are still different disciplines. "A scientist can discover a new star, but he cannot make one. He would have to ask an engineer to do it for him.". –Gordon Lindsay Glegg, The Design of Design (1969). A few months ago, I wrote about the differences between data engineers and data scientists. I talked about their skills and common starting points.
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Analytics Vidhya
DECEMBER 15, 2019
Overview Neural fake news (fake news generated by AI) can be a huge issue for our society This article discusses different Natural Language Processing. The post An Exhaustive Guide to Detecting and Fighting Neural Fake News using NLP appeared first on Analytics Vidhya.
CIO Business Intelligence
APRIL 9, 2019
Business intelligence (BI) analysts transform data into insights that drive business value. Through use of data analytics, data visualization and data modeling techniques and technologies, BI analysts can identify trends that can help other departments, managers and executives make business decisions to modernize and improve processes in the organization.
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.
KDnuggets
NOVEMBER 28, 2019
Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.
erwin
NOVEMBER 28, 2019
Enterprise architecture tools are becoming more important than ever. The International Enterprise Architecture Institute (IEAI) defines enterprise architecture (EA) as “the analysis and documentation of an enterprise in its current and future states from an integrated strategy, business and technology perspective.”. In the era of data-driven business, such perspective is critical.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Smart Data Collective
NOVEMBER 28, 2019
Businesses can use big data in many capacities, but those who use it for social media are at a huge advantage. It enables you as a social media marketer to get a closer look at your customer base, understand what drives purchasing decisions , and encourage consumers to pull the trigger. Using big data to augment your social media strategy provides a wealth of opportunities simply because social media is such an integral part of people’s lives.
ScienceSoft
MAY 10, 2019
Explore five different types of artificial intelligence (AI) – analytic, interactive, text, visual and functional – and get inspired by real-life business examples of AI in action.
DataCamp
OCTOBER 1, 2019
This cheat sheet guides you through the basics of how data science can help your business, including building your data science team and the common steps in the data science workflow.
Domino Data Lab
MAY 15, 2019
This Domino Data Science Field Note covers Pete Skomoroch ’s recent Strata London talk. It focuses on his ML product management insights and lessons learned. If you are interested in hearing more practical insights on ML or AI product management, then consider attending Pete’s upcoming session at Rev. Machine Learning Projects are Hard: Shifting from a Deterministic Process to a Probabilistic One.
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.
datapine
MAY 14, 2019
“Big data is at the foundation of all the megatrends that are happening.” – Chris Lynch, big data expert. We live in a world saturated with data. At present, around 2.7 Zettabytes of data are floating around in our digital universe, just waiting to be analyzed and explored, according to AnalyticsWeek. By gaining the ability to understand, quantify, and leverage the power of online data analysis to your advantage, you will gain a wealth of invaluable insights that will help your business flourish
O'Reilly on Data
DECEMBER 10, 2019
Roughly a year ago, we wrote “ What machine learning means for software development.” In that article, we talked about Andrej Karpathy’s concept of Software 2.0. Karpathy argues that we’re at the beginning of a profound change in the way software is developed. Up until now, we’ve built systems by carefully and painstakingly telling systems exactly what to do, instruction by instruction.
Analytics Vidhya
DECEMBER 26, 2019
Introduction “Ripley’s Believe or Not” features some of the weirdest and most bizarre facts from around the world. How about creating our own Ripley’s. The post 5 Weird and Hilarious Uses of Data Science appeared first on Analytics Vidhya.
CIO Business Intelligence
JUNE 13, 2019
Salesforce.com’s $15.7 billion bid for Tableau Software has many organizations wondering how the proposed acquisition will impact their operations. According to industry analysts, it all depends on how your enterprise makes use of their respective platforms. Users of Salesforce’s CRM platform have all subscribed to its software-as-a-service (SaaS) model, putting their data in the cloud — but the company is only beginning to respond to the demand for sophisticated tools to analyze that data. [ De
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.
KDnuggets
DECEMBER 6, 2019
Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.
erwin
SEPTEMBER 5, 2019
Why planning your 5G roadmap requires significant input from enterprise architects. 5G is coming and bringing with it the promise to transform any industry. And while the focus has been on the benefits to consumers, the effects on the enterprise are far- reaching. Few examples of emerging technology have the potential to disrupt and downright revolutionize certain markets and processes than 5G.
Data Science 101
NOVEMBER 29, 2019
Initiative for Analytics and Data Science Standards (IADSS) is an organization working to develop standards around the roles in data science. They did a large survey earlier this year and they are starting to role out some of their results. Below is a video with some early results. Great Stuff! Data Science 101 is proud to be an IADSS Digital Community Partner.
Smart Data Collective
NOVEMBER 21, 2019
Big data is transforming the daily realities of running a business. Companies can use big data to handle certain tasks more quickly and cost-effectively than ever. Vince Campisi, CIO of GE Software, Ash Gupta, an executive with American Express, and many other companies use big data to get a competitive advantage. Of course, big data also raises some new challenges.
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MLWhiz
APRIL 18, 2019
Visualizations are awesome. However, a good visualization is annoyingly hard to make. Moreover, it takes time and effort when it comes to present these visualizations to a bigger audience. We all know how to make Bar-Plots, Scatter Plots, and Histograms, yet we don’t pay much attention to beautify them. This hurts us?-?our credibility with peers and managers.
DataRobot Blog
APRIL 22, 2019
by Jen Underwood. So many buzzwords, so much confusion. Automated analytics, artificial intelligence (AI)-driven BI, and automated machine learning (AutoML), aren’t these terms describing the exact same thing? NO. Although these technologies may. Read More.
Dataiku
JULY 4, 2019
It's hard to know where to start once you’ve decided that yes, you want to dive into the fascinating world of data and AI. Just looking at all the technologies you have to understand and all the tools you’re supposed to master is enough to make your dizzy.
datapine
JUNE 5, 2019
“It is a capital mistake to theorize before one has data.”– Arthur Conan Doyle. Data is all around us. According to the EMC Digital Universe study, by 2020, around 40 trillion megabytes – or 40 zettabytes – will exist in our digital landscape. That’s an unfathomable amount of information. Data has changed our lives in many ways, helping to improve the processes, initiatives, and innovations of organizations across sectors through the power of insight.
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Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. That’s what drove the five companies in this e-book to change their approach to analytics. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.
O'Reilly on Data
FEBRUARY 4, 2019
How companies in Europe are preparing for and adopting AI and ML technologies. In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. In practice this means developing a coherent strategy for integrating artificial intelligence (AI), big data, and cloud components, and specifically investing in foundational technologies needed to sustain the sensible use of da
Analytics Vidhya
DECEMBER 29, 2019
Introduction The stock of a data scientist is at an all-time high right now. There aren’t too many professions out there that can rival. The post 5 Key Reasons Why Data Scientists Are Quitting their Jobs appeared first on Analytics Vidhya.
Sisense
APRIL 24, 2019
In organizations that operate without a data warehouse or separate analytical database for reporting, the only source of the latest and up-to-date data may be in the live production database. When querying a production database, optimization is key. An inefficient query may pose a burden on the production database’s resources, and cause slow performance or loss of service for other users if the query contains errors.
KDnuggets
DECEMBER 26, 2019
Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.
Speaker: Keith Kmett, Principal CX Advisor at Medallia
Join Keith Kmett, Principal CX Advisor, in this new webinar that will focus on: Understanding CX Orchestration Fundamentals: Gain a solid understanding of what CX orchestration is, its significance in the customer experience landscape, and how it plays a crucial role in shaping customer journeys. This includes the key concepts, strategies, and best practices involved in CX orchestration. 🔑 Connection to Customer Journey Maps: How to effectively integrate customer journey mapping into the
erwin
AUGUST 22, 2019
The design thinking process is a method of encouraging and improving creative problem-solving. The design thinking process is by no means new. John Edward Arnold, a professor of mechanical engineering and business administration, was one of the first to discuss the concept in as early as the 1950s. But the wave of digital and data-driven business has created new opportunities for the design thinking process to be applied.
Data Science 101
NOVEMBER 29, 2019
In the United States, it is a holiday week, so the news is pretty limited from many of the big cloud providers. Luckily, Amazon has come through with a flurry of machine learning announcements. Amazon is holding their annual re:Invent Conference next week, so maybe these announcements are precursors to some bigger news next week. We will have to wait and see.
Smart Data Collective
JULY 30, 2019
In an earlier age, perhaps as little as a decade ago, businesses had to rely on intuition and educated guesses to guide their spending. The situation was famously captured by John Wanamaker, who said, “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.” Today, data is everywhere. Phones track our locations and our social media usage.
Domino Data Lab
JULY 10, 2019
Joshua Poduska provides a distilled overview of Ludwig including when to use Ludwig’s command-line syntax and when to use its Python API. Introduction. New tools are constantly being added to the deep learning ecosystem. It can be fun and informative to look for trends in the type of tools being created. For example, there have been multiple promising tools created recently that have Python APIs, are built on top of TensorFlow or PyTorch , and encapsulate deep learning best practices to allow d
Advertiser: Data Robot
The buzz around generative AI shows no sign of abating in the foreseeable future. Enterprise interest in the technology is high, and the market is expected to gain momentum as organizations move from prototypes to actual project deployments. Ultimately, the market will demand an extensive ecosystem, and tools will need to streamline data and model utilization and management across multiple environments.
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