Smart Data Collective
JULY 25, 2019
Not long ago, big data was one of the most talked about tech trends , as was artificial intelligence (AI). But, in case people need a reminder of how fast technology evolves , they only need to consider something newer — big data AI. It combines elements of both technologies. AI allows computers to perform cognitive functions, much like the human brain.
DataRobot Blog
JULY 9, 2019
by Jen Underwood. To retain market leadership in the algorithm economy, enterprises require new ways to maximize the value of data and AI with citizen data scientists. Don’t think citizen data science is. Read More.
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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.
BA Learnings
JULY 18, 2019
I tend to describe the agile approach as a way of working; A targeted way of working that allows us to make changes, respond to customers’ needs and manage uncertainty with minimal delays, and without needing to wade through “red tape”. Agile manifesto encourages: - Customer collaboration over contract negotiation - Individuals and interactions over processes and tools - Responding to change over following a plan - Working software over full documentation This does not however imply that the agi
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.
Jet Global
JULY 2, 2019
The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive. What was at first a data stream has morphed into a data river as enterprise businesses are harvesting reams of data from every conceivable input across every conc
Peter James Thomas
JULY 24, 2019
I was asked the question appearing in the title of this short article recently and penned a reply, which I thought merited sharing with a wider audience. Here is an expanded version of what I wrote: Let’s start by considering some related questions: Why are so many businesses still doing a bad job of controlling their costs in 2019? Why are so many businesses still doing a bad job of integrating their acquisitions in 2019?
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Analytics Vidhya
JULY 31, 2019
Overview Managing the various stakeholders in a data science project is a must-have aspect for a leader Delivering an end-to-end data science project is. The post A Data Science Leader’s Guide to Managing Stakeholders appeared first on Analytics Vidhya.
datapine
JULY 17, 2019
Experts predict that by 2025, around 175 Zettabytes of data will be generated annually, according to research from Seagate. Moreover, within just five years, the number of smart connected devices in the world will amount to more than 22 billion – all of which will produce colossal sets of collectible, curatable, and analyzable data, claimed IoT Analytics in their industry report.
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.
Teradata
JULY 9, 2019
Integrated data and analytics has a proven track record of helping organize operations, enhance customer experience and improve revenue and market growth.
Speaker: David Bard, Principal at VP Product Coaching
In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.
Jet Global
JULY 11, 2019
With major advances being made in artificial intelligence and machine learning, businesses are investing heavily in advanced analytics to get ahead of the competition and increase their bottom line. One of those areas is called predictive analytics, where companies extract information from existing data to determine buying patterns and forecast future trends.
Corinium
JULY 7, 2019
Drawing on over 30 years of experience, we caught up with our international keynote, Cary Correia, Chief Commercial Data Scientist, GE USA to share some golden nuggets on how to truly achieve a data-driven culture and become an intelligent enterprise. See how Cary’s teams worked towards a data driven culture, the use of proactive and reactive analytics, and facilitating the most significant steps to move from strategy to execution.
Analytics Vidhya
JULY 29, 2019
Overview Recommendation engines are ubiquitous nowadays and data scientists are expected to know how to build one Word2vec is an ultra-popular word embeddings used. The post Building a Recommendation System using Word2vec: A Unique Tutorial with Case Study in Python appeared first on Analytics Vidhya.
datapine
JULY 31, 2019
In a data-driven age, modern organizations need access to advanced data analytics solutions to help them improve the business in a wealth of key areas—Salesforce is one of those solutions. One of the world’s most popular cloud-based customer relationship management (CRM) platforms, the software is designed to help companies across sectors plan and optimize their sales processes.
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.
Rocket-Powered Data Science
JULY 7, 2019
Career Relevance. Definitions of terminology frequently seen and used in discussions of emerging digital technologies. (NOTE: This page is a WIP = Work In Progress.). AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data).
David Menninger's Analyst Perspectives
JULY 26, 2019
Alteryx Inspire 2019, this year's user conference for Alteryx, drew around 4500 customers, partners, and prospects to Nashville’s Gaylord Opryland Resort & Convention Center in Tennessee last month. The strong attendance was a reflection of the strong growth Alteryx has experienced over the last year; roughly 50% growth year-over-year. This year's conference focused on Alteryx's evolution from data preparation to AI and machine learning, and both were front and center.
O'Reilly on Data
JULY 18, 2019
The O’Reilly Data Show Podcast: Roger Chen on the fair value and decentralized governance of data. In this episode of the Data Show , I spoke with Roger Chen, co-founder and CEO of Computable Labs , a startup focused on building tools for the creation of data networks and data exchanges. Chen has also served as co-chair of O'Reilly's Artificial Intelligence Conference since its inception in 2016.
KDnuggets
JULY 26, 2019
Different neural network architectures excel in different tasks. This particular article focuses on crafting convolutional neural networks in Python using TensorFlow and Keras.
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Analytics Vidhya
JULY 18, 2019
Overview We look at the latest state-of-the-art NLP library in this article called PyTorch-Transformers We will also implement PyTorch-Transformers in Python using popular NLP. The post Introduction to PyTorch-Transformers: An Incredible Library for State-of-the-Art NLP (with Python code) appeared first on Analytics Vidhya.
erwin
JULY 12, 2019
In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. News broke earlier this week of British Airways being fined 183 million pounds – or $228 million – by the U.K. for alleged violations of the European Union’s General Data Protection Regulation (GDPR).
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
David Menninger's Analyst Perspectives
JULY 23, 2019
Summit 2019, Information Builders' annual user conference, drew about 1000 attendees this year, including customers, partners and prospects all working with Information Builders' technologies. Under new leadership, Summit 2019 showcased the direction Information Builders is moving in the next couple of years.
Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO
The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.
Smart Data Collective
JULY 9, 2019
Business success begins and ends with customer experience. According to recent studies, 90 percent of buyers would gladly spend more for a better customer experience. That’s exactly why understanding what an improved experience means for customers is so important. Companies have been able to perform more in-depth customer analysis—above and beyond social media commentary and feedback surveys—with the development and proliferation of analytics.
KDnuggets
JULY 29, 2019
Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.
Analytics Vidhya
JULY 15, 2019
Overview We are the in middle of a golden age of machine learning applications Here’s a comprehensive list of popular and common machine learning. The post The Ultimate List of Popular Machine Learning Use Cases in our Day-to-Day Life appeared first on Analytics Vidhya.
MLWhiz
JULY 29, 2019
Data Science is the study of algorithms. I grapple through with many algorithms on a day to day basis so I thought of listing some of the most common and most used algorithms one will end up using in this new DS Algorithm series. This post is about some of the most common sampling techniques one can use while working with data. Simple Random Sampling Say you want to select a subset of a population in which each member of the subset has an equal probability of being chosen.
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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.
Domino Data Lab
JULY 22, 2019
Paco Nathan presented, “Data Science, Past & Future” , at Rev. This blog post provides a concise session summary, a video, and a written transcript. Session Summary. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.
erwin
JULY 11, 2019
At a fundamental level, digital transformation is about further synthesizing an organization’s operations and technology, so involving business architecture and process modeling is a best practice organizations cannot ignore. This post outlines how business architecture and process modeling come together to facilitate efficient and successful digital transformation efforts.
Cloudera
JULY 10, 2019
Open source has been core to the missions of both Hortonworks and Cloudera and central to our values and culture. With more than 700 engineers in the new Cloudera, our company writes a prodigious amount of open source code each year that’s contributed to more than 30 different open source projects. We’re also a very innovative open source company, having collectively launched more than a dozen new open source projects since the founding of the two companies. .
KDnuggets
JULY 24, 2019
Recently, researchers from the Google Brain team published a paper proposing a new method called Concept Activation Vectors (CAVs) that takes a new angle to the interpretability of deep learning models.
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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