October, 2022

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P&G turns to AI to create digital manufacturing of the future

CIO Business Intelligence

Over the past 184 years, The Procter & Gamble Co. (P&G) has grown to become one of the world’s largest consumer goods manufacturers, with worldwide revenue of more than $76 billion in 2021 and more than 100,000 employees. Its brands are household names, including Charmin, Crest, Dawn, Febreze, Gillette, Olay, Pampers, and Tide. In summer 2022, P&G sealed a multiyear partnership with Microsoft to transform P&G’s digital manufacturing platform.

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What We Learned Auditing Sophisticated AI for Bias

O'Reilly on Data

A recently passed law in New York City requires audits for bias in AI-based hiring systems. And for good reason. AI systems fail frequently, and bias is often to blame. A recent sampling of headlines features sociological bias in generated images , a chatbot , and a virtual rapper. These examples of denigration and stereotyping are troubling and harmful, but what happens when the same types of systems are used in more sensitive applications?

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Three R Libraries for Automated EDA

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction With the increasing use of technology, data accumulation is faster than ever due to connected smart devices. These devices continuously collect and transmit data that can be processed, transformed, and stored for later use. This collected data, known as big data, holds valuable […].

Big Data 399
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Podcast: Scaling DataOps

DataKitchen

The post Podcast: Scaling DataOps first appeared on DataKitchen.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

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.

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Easy Guide To Data Preprocessing In Python

KDnuggets

Preprocessing data for machine learning models is a core general skill for any Data Scientist or Machine Learning Engineer. Follow this guide using Pandas and Scikit-learn to improve your techniques and make sure your data leads to the best possible outcome.

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AI Data, Traditional Trading, and Modern Investments

Smart Data Collective

Artificial intelligence is drastically changing the future of finance. Financial institutions spent over $10.1 billion on AI last year. One of the many ways that AI is being leveraged in finance is by helping improve the experience of investors. Modern investors enjoy a much smoother trading experience than their predecessors. Thanks to the invention of the internet, everything from conducting trades to downloading comprehensive reports can be completed almost instantly.

Finance 135

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Do You Need a Single Map, or Several Maps?

Depict Data Studio

Here’s a counterintuitive dataviz principle: Sometimes, it’s easier to understand several small graphs than a single graph. I was recently working with an organization to visualize which states were using their software programs. States might use: Software A Software B Or, both software A and B. Before: A Single Multicolor Map. Here’s what their visualization looked like.

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Data Science Tools for Vaccine Design and Development

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Biopharmaceutical Industries are the fastest growing industries after considering the basic need for the healthy life of humans and animals. Based on the available literature, the author has identified six major thrust areas of the Biopharmaceutical industry, which has summarized in the […].

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6 Myths About Visual Data Tools

Dataiku

This is a guest article from Lontia Nkhuwa. Nkhuwa is a product support lead and technical writer. She's the leader of PyLadies Lusaka — a support network for women in the world of Phyton. Lontia is passionate about creating content that educates, grows, and inspires leaders. In her spare time, Lontia enjoys thrifting and traveling.

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Frameworks for Approaching the Machine Learning Process

KDnuggets

This post is a summary of 2 distinct frameworks for approaching machine learning tasks, followed by a distilled third. Do they differ considerably (or at all) from each other, or from other such processes available?

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

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.

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AI Tools Make Short-Selling Possible with Algorithmic Trading

Smart Data Collective

Artificial intelligence is driving a number of changes in the financial sector. We pointed out that AI has created new opportunities for investors purchasing real estate stocks. However, it is also creating unique trading opportunities for those using nontraditional investing decisions. One of the ways that smart investors can use AI is with short-selling.

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7 ways to foster IT innovation

CIO Business Intelligence

As an IT leader, being able to foster innovation not only benefits the IT itself, with greater efficiency, effectiveness and value, but the organization it serves and you personally, as it illustrates your ability to be an internal agent of change, a true business partner, and an asset at the strategy table. 1. Define and articulate your definition of IT innovation.

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How to Make a Not-So-Scary Starter Dashboard in Excel

Depict Data Studio

Dashboards aren’t scary! In this video, let’s make a starter dashboard in Microsoft Excel. You’ll learn how to make four quick visuals: Sparklines Data bars Symbol fonts Color scales. I use these visuals over and over in my real-life consulting projects. Watch the Tutorial. Sparklines. Sparklines are helpful for visualizing patterns over time, like daily, weekly, monthly, quarterly, or annual data.

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An Overview of Graph Machine Learning and Its Working

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Graph machine learning is quickly gaining attention for its enormous potential and ability to perform extremely well on non-traditional tasks. Active research is being done in this area (being touted by some as a new frontier of machine learning), and open-source libraries […].

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

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.

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ClearScape Analytics: Delivering Value Across the Modern Enterprise

Teradata

ClearScape Analytics provides robust functionality giving people across the organization the ability to efficiently execute their roles in the analytics process on a common platform.

Analytics 105
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Sparse Matrix Representation in Python

KDnuggets

Leveraging sparse matrix representations for your data when appropriate can spare you memory storage. Have a look at the reasons why, see how to create sparse matrices in with Python, and compare the memory requirements for standard and sparse representations of the same data.

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Cloud Technology Helps Students Earn Higher SAT Scores

Smart Data Collective

Cloud technology is changing some of the most core aspects of our lives. A growing number of students are finding ways to leverage the cloud to improve their learning experience. Education Technology Magazine has published an article on some of the most surprising ways that cloud technology is changing academia. Most of their focus was on their focus has been on the benefits of using cloud technology from the standpoint of educators.

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What is transformational leadership? A model for motivating innovation

CIO Business Intelligence

What is transformational leadership? The transformational leadership approach encourages, inspires, and motivates employees to innovate and create the change necessary to shape the future success of the company. This is accomplished by setting an example at the executive level through authenticity, a strong sense of corporate culture, employee ownership, and independence in the workplace.

Modeling 145
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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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Stop Using Tiny, Grainy Photos in PowerPoint!!!

Depict Data Studio

It’s not 1995. Last week, I was leading a post-conference workshop with CQI professionals in California. You can learn more about their annual conferences here. An attendee asked about best practices for adding photographs to our PowerPoint presentations. Before. Let’s pretend that you’re giving a presentation about young children and physical fitness.

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Blockchain and Deploying Applications on Docker and Kubernetes

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Niti Ayog, one of the transforming national institutions, has published an article on Blockchain use cases in India. Few questions about Blockchain, why Blockchain, and how we can deploy our applications through the docker and Kubernetes we should know. Objectives We will discuss […].

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AI Governance: Break open the black box

IBM Big Data Hub

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. Today, AI presents an enormous opportunity to turn data into insights and actions, to amplify human capabilities, decrease risk and increase ROI by achieving break through innovations. While the promise of AI isn’t guaranteed and doesn’t always come easy, adoption is no longer a choice.

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How to Build a Data Science Enablement Team: A Complete Guide

KDnuggets

A Data Science Enablement Team consists of people from various departments like marketing, sales, product development, etc. They are responsible for providing the necessary tools and resources to help the data scientists do their job more efficiently.

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Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity

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.

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How Formula 1 Teams Leverage Big Data for Success

Smart Data Collective

We have previously talked about ways that big data is changing the world of sports. Formula 1 teams are among those most affected. Ever since the Oakland A’s switched their recruitment policy from a players’ running speed and strength to a more sophisticated and nuanced look at the on-base slugging percentage, the world of sports has become more and more accustomed to utilizing sports analytics in their team-building.

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Chipotle’s recipe for digital transformation: Cloud plus AI

CIO Business Intelligence

When Curt Garner became Chipotle’s first CIO in 2015, the only technology used for online restaurant ordering was, “believe it or not,” a fax machine, he says. Seven years later, the Newport Beach, Calif.-based company is piloting a system with a robotic arm dubbed “Chippy” that prepares the fast-casual chain’s famed fried salt-and-lime chips homemade every day without human labor, with the aim of tailoring output to the daily needs of each restaurant.

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What’s the Pharmaverse, and How Do Data Science Innovators Use It to Streamline Drug Approvals?

Domino Data Lab

When it comes to the pharmaceutical industries, machine learning, AI, and statistical computing environments (SCEs) often receive the lion’s share of media attention and seize the popular imagination in coverage that focuses mostly on technology aimed at finding interesting chemical candidates for the next breakthrough cure. But there’s a second, far more rarely covered role of data science in the quest for new cures, one that Andy Nicholls, GSK’s senior director and head of statistical data sci

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A Quick Guide to Blockchain: Merkle Tree

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction A Merkle tree is a basic component of blockchain technology. It is a mathematical data structure composed of hashes of different data blocks that serve as a summary of all transactions in the block. It also enables efficient and secure verification of […]. The post A Quick Guide to Blockchain: Merkle Tree appeared first on Analytics Vidhya.

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The Big Payoff of Application Analytics

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.

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The Data Warehouse is Dead, Long Live the Data Warehouse, Part I

Data Virtualization

Reading Time: 4 minutes “Le roi est mort, vive le roi.” This phrase—the king is dead, long live the king—marks the transfer of power from one monarch to the next. In times of potentially troublesome change, the apparent paradox and inner poetry of these. The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

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The Complete Free PyTorch Course for Deep Learning

KDnuggets

Do you want to learn PyTorch for machine learning and deep learning? Check out this 24 hour long video course with accompanying notes and courseware for free. Did I mention it's free?

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How To Keep Your Data Security Knowledge Up To Date?

Smart Data Collective

The fast-paced world of cybersecurity waits for none, and even seasoned professionals can find that years have passed them by if they take a short hiatus and stop staying up to date. Given the nature of this sector, it’s often compared with statecraft, with the constantly evolving threat matrix making it essential to stay on top of developments, and regularly upskill in order to better respond to challenges.

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What transformational leaders too often overlook

CIO Business Intelligence

High-performing CIOs know that digital mastery depends on a strong foundation of rock-solid infrastructure, information security, enterprise data management, and sound IT governance. But for all the emphasis on cutting-edge technology for business transformation, IT infrastructure too often gets short shrift. Infrastructure, what happens behind the IT screen, and related support activities remains poorly understood, underappreciated, and mismanaged in 89% of enterprises today, according to a rec

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Addressing Top Enterprise Challenges in Generative AI with DataRobot

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.