Tue.Mar 24, 2020

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Using Graphs to Identify Social Media Influencers

Analytics Vidhya

Overview Learn how to use graphs to identify social media influencers We will demonstrate several techniques to identify these social media influencers and lay. The post Using Graphs to Identify Social Media Influencers appeared first on Analytics Vidhya.

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Why BERT Fails in Commercial Environments

KDnuggets

The deployment of large transformer-based models in dynamic commercial environments often yields poor results. This is because commercial environments are usually dynamic, and contain continuous domain shifts between inference and training data.

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6 Python Libraries to Interpret Machine Learning Models and Build Trust

Analytics Vidhya

The Case for Building Trust in Machine Learning Models There are approximately 1.2 billion vehicles on the roads around the world. Here’s a bamboozling. The post 6 Python Libraries to Interpret Machine Learning Models and Build Trust appeared first on Analytics Vidhya.

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5 Ingenious Ways To Use Big Data For Customer Engagement

Smart Data Collective

Big data is changing the direction of our economy in unprecedented ways. Every business should look for ways to monetize big data and use it to optimize your business model. The number of companies using big data is growing at an accelerated rate. One poll found that 53% of businesses were using big data analytics in 2017. This figure has presumably risen in the years since.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

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.

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Why Analytics Are Essential in Times of Crisis

Sisense

Blog. In Navigating Change in Crisis, we explore how individuals and companies are adapting to a “new normal” in order to keep essential services functioning. We provide actionable advice around how organizations, and ultimately the builders of data and analytic apps, are adapting to meet these changes. These insights aim to help you and your team navigate these unprecedented times.

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Business Process Modeling Use Case: Disaster Recovery

erwin

In these challenging times, many of our customers are focused on disaster recovery and business contingency planning. Disaster recovery is not just an event but an entire process defined as identifying, preventing and restoring a loss of technology involving a high-availability, high-value asset in which services and data are in serious jeopardy. Technical teams charged with maintaining and executing these processes require detailed tasks, and business process modeling is integral to their docum

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Top AI Resources – Directory for Remote Learning

KDnuggets

Whether you are just learning Data Science, a current professional, or just interested, it's crucial to keep the mind stimulated and stay current. With conferences, schools, and travel largely canceled because of #coronavirus, these remote resources will help you stay engaged.

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How to Use Payroll Headcount Ratios (+ Downloadable Template)

Jet Global

With low unemployment rates and widespread talent shortages in many in-demand fields, employees are one of the most important assets at today’s companies. They’re important because talent helps distinguish one company from another, becoming a key part of a company’s competitive advantage. However, they’re also important because employees are a major expense that requires careful management.

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Graph Neural Network model calibration for trusted predictions

KDnuggets

In this article, we’ll talk about calibration in graph machine learning, and how it can help to build trust in these powerful new models.

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New Coronavirus (COVID-19) Daily Updates Report

Paul Turley

After publishing the original daily COVID-19 cases report on March 14, Johns Hopkins University changed the file format. This required us to publish an updated dataset with a new report, which you can access here. Since the original solution was posted, I have received a tremendous amount of feedback, suggestions for enhancements and corrections.

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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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Why the corona-crisis will accelerate corporate digital transformations

Mark Raskino

Pick any piece of software you have been using today. What version number is it… 3.1, 5,2, 10.1 perhaps? We think contemporary digital change is fast, but it is nothing compared to the pace of innovation during war. Over the six years of World War II an incredible 24 versions, or ‘marks’ of the Supermarine Spitfire aircraft were produced.

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Data Science Papers for Spring 2020

Data Science 101

The world of data science is rapidly evolving. Here are a few data science papers I have found interesting. What’s Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities This paper is a study done on the usage of notebooks for data science. It cover a bunch of the negative impacts of using notebooks for data science. Deployment, setup, collaboration, and reliablity are a few of the examples.

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Can AI help in fighting against Corona?

MLWhiz

Feeling Helpless? I know I am. With the whole shutdown situation, what I thought was once a paradise for my introvert self doesn’t look so good when it is actually happening. I really cannot fathom being at home much longer. And this feeling of helplessness at not being able to do anything doesn’t help. Honestly, I would like to help with so much more in this dire situation, but here are some small ideas around which we as AI practitioners and Data Scientists can be of use.

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Advice for Early-Career Data Visualization Freelancers: Ann’s Interview with Jane Zhang

Depict Data Studio

When Jane Zhang wanted to interview me for her article for the Data Visualization Society, I agreed! We decided to record our conversation so that even more people could benefit from learning about the business behind my business. This conversation might be especially helpful for early-career data visualization freelancers—or those contemplating the switch from a salaried job into a freelancing job.

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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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Healthcare Bot Helps Providers Manage COVID-19 Inquiries

CDW Research Hub

As the COVID-19 pandemic reaches into more communities, many hospitals, clinics and providers are being inundated with inquiries from people who are concerned they may have been exposed and need treatment. To prevent healthcare organizations from being overwhelmed by inquiries, and to ensure that only those who truly need help enter the system, it is essential to screen inquiries in a way that assesses an individual’s potential risk, then directs any qualified risk cases to the appropriate resou

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What is BI Intelligence?

Octopai

Business Intelligence has a lot depending on it. Every time someone from Marketing or Sales or HR needs a report created or modified, or every time there’s a problem with some data in a report that needs to be sorted ASAP – who do you call? BI, obviously. But, with the amount of time it takes for BI to deliver and the amount of manual data mapping and tracing required to enable accurate delivery, you have to question if maybe BI could be made more intelligent.

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Don’t let panic worsen the COVID-19 crisis: Let data run the supply chain

Teradata

Understanding the supply chain and how panic buying not only worsens the situation but also has long term impact on forecasting and demand models.

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Our Top 20 Most-Read Data and Analytics Research Last Week (to Mar 22)

Andrew White

Click here for an interactive PDF to connect to the most read data and analytics research directly. This list excludes our branded research such as Magic Quadrants etc. Carlie Idoine , our new Key Initiative leader for Analytics, BI and Data Science solutions, just published a note concerning the market collision taking place across all of data and analytics.

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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Snowflake and DataRobot: No “Cooler” Tech Stack

DataRobot

I recently had the opportunity to speak at a number of Data For Breakfast events as part of DataRobot’s strategic partnership with Snowflake. The event series delivers content and best practices on advancements in cloud data analytics and data science. Since I usually skip breakfast – intermittently fasting in a desperate attempt to be healthy – I was glad to find intellectual nourishment was on the menu too, complementing the generous rashes of bacon and three-egg omelets!

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The Incredibly Important Role Of Big Data In Academia

Smart Data Collective

One of the most important elements in the evolution of the education system is the ability to make informed conclusions about the need to change approaches that are used and the actions that are taken. According to a 2015 whitepaper published in Science Direct , big data is one of the most disruptive technologies influencing the field of academia. The educational system continuously creates and accumulates a significant amount of data, and the question of the systematic work with these data by a

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Effective Collaboration Through Dashboards When It Matters Most

Sisense

Blog. In Navigating Change in Crisis, we explore how individuals and companies are adapting to a “new normal” in order to keep essential services functioning. We provide actionable advice around how organizations, and ultimately the builders of data and analytic apps, are adapting to meet these changes. These insights aim to help you and your team navigate these unprecedented times.

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The unreasonable importance of data preparation

O'Reilly on Data

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. This is the garbage in, garbage out principle: flawed data going in leads to flawed results, algorithms, and business decisions. If a self-driving car’s decision-making algorithm is trained on data of traffic collected during the day, you wouldn’t put it on the roads at night.

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Driving Business Impact for PMs

Speaker: Jon Harmer, Product Manager for Google Cloud

Move from feature factory to customer outcomes and drive impact in your business! This session will provide you with a comprehensive set of tools to help you develop impactful products by shifting from output-based thinking to outcome-based thinking. You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap.