Sat.Mar 21, 2020 - Fri.Mar 27, 2020

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Coronavirus Data and Poll Analysis – yes, there is hope, if we act now

KDnuggets

We examine the growth of coronavirus daily cases in most affected countries, and show evidence that social distancing works in reducing the rate of spread. We also analyze KDnuggets Poll results - the scale of change to online and how Data Science work is likely to increase or drop in different regions. Stay Healthy and practice social distancing!

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Behind The Scenes Of The Linode Object Storage Service

Data Engineering Podcast

Summary There are a number of platforms available for object storage, including self-managed open source projects. But what goes on behind the scenes of the companies that run these systems at scale so you don’t have to? In this episode Will Smith shares the journey that he and his team at Linode recently completed to bring a fast and reliable S3 compatible object storage to production for your benefit.

Media 100
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ksqlDB: The Missing Link Between Real-Time Data and Big Data Streaming

Confluent

Is event streaming or batch processing more efficient in data processing? Is an IoT system the same as a data analytics system, and a fast data system the same as […].

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Five Books Every CX Leader Should Read in this Time of Social Distancing

Teradata

Check out this curated reading list of books on customer experience. From updated classics to new research and insights into how large enterprises can drive business outcomes from a CX initiative.

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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 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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Learn to Optimize Algorithms in Our New Algorithm Complexity Course

Dataquest

Algorithms are at the center of almost any programming job. And particularly in the world of data engineering, using efficient algorithms is important enough that it’s a common topic to be quizzed about in job interviews. That’s why we’ve just launched a new course! Algorithm Complexity is the latest course in our Data Engineer career path.

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Nordea Bank

Teradata

Applying cognitive automation to keep pace with increasingly complex financial regulations and consumer expectations.

Banking 52
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Exploring TensorFlow Quantum, Google’s New Framework for Creating Quantum Machine Learning Models

KDnuggets

TensorFlow Quantum allow data scientists to build machine learning models that work on quantum architectures.

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Evaluating Ray: Distributed Python for Massive Scalability

KDnuggets

If your team has started using ?Ray? and you’re wondering what it is, this post is for you. If you’re wondering if Ray should be part of your technical strategy for Python-based applications, especially ML and AI, this post is for you.

Python 99
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Made With ML: Discover, build, and showcase machine learning projects

KDnuggets

This is a short introduction to Made With ML, a useful resource for machine learning engineers looking to get ideas for projects to build, and for those looking to share innovative portfolio projects once built.

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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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Diffusion Map for Manifold Learning, Theory and Implementation

KDnuggets

This article aims to introduce one of the manifold learning techniques called Diffusion Map. This technique enables us to understand the underlying geometric structure of high dimensional data as well as to reduce the dimensions, if required, by neatly capturing the non-linear relationships between the original dimensions.

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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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Want to Build an AI Model for Your Business? Read this

KDnuggets

The best approach for AI production is similar to what venture capitalists (VC’s) do when they evaluate and invest in startups.

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Alternative Data, Text Analytics, and Sentiment Analysis in Trading and Investing

KDnuggets

Different types of data beyond your typical dollars and cents have been used in the finance industry for many years. By leveraging machine learning, sentiment data is expected to play an increasingly dominant role in the investment industry, and this article highlights some special challenges of its use in trading models.

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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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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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How to Make Remote Work Effective for Data Science Teams

KDnuggets

This post aims to highlight some work from home best practices, both general and data science-specific, in order to help data scientists and teams remain productive, connected and happy while working remotely.

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How to Make Your Open Source Apache Kafka Connector Available on Confluent Hub

Confluent

Do you have data you need to get into or out of Apache Kafka®? Kafka connectors are perfect for this. There are many connectors out there, usually for well-known and […].

Kafka 59
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Top Stories, Mar 16-22: 24 Best (and Free) Books To Understand Machine Learning

KDnuggets

Also: Time Series Classification Synthetic vs Real Financial Time Series; Nine lessons learned during my first year as a Data Scientist; What is the most effective policy response to the new coronavirus pandemic?; Nine lessons learned during my first year as a Data Scientist; Five Interesting Data Engineering Projects.

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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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KDnuggets™ News 20:n12, Mar 25: 24 Best (and Free) Books To Understand Machine Learning; Coronavirus Daily Change and Poll Analysis; 9 lessons learned during 1st year as a Data Scientist

KDnuggets

Read our analysis of coronavirus data and poll results; Use your time indoors to learn with 24 best and free books to understand Machine Learning; Study the 9 important lessons from the first year as a Data Scientist; Understand the SVM, a top ML algorithm; check a comprehensive list of AI resources for online learning; and more.

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Top KDnuggets tweets, Mar 18-24: Advice to Data Scientists: don’t post a blog on #coronavirus based on your ad-hoc data analysis without reading something on epidemiology – here are some useful links

KDnuggets

#Coronavirus growth in Western countries: March 19 update - Spain and US cases; If you need a break from #coronavirus news, here is #AlphaGo - The Movie; Which Country Has Flattened the Curve for the #Coronavirus?; Excellent source of #Coronavirus info - FT.

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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.

Data 45