Wed.Dec 18, 2019

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30 Challenging Open Source Data Science Projects to Ace in 2020

Analytics Vidhya

Overview Check out our pick of the 30 most challenging open-source data science projects you should try in 2020 We cover a broad range. The post 30 Challenging Open Source Data Science Projects to Ace in 2020 appeared first on Analytics Vidhya.

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AI is computer science disguised as hard work

O'Reilly on Data

Roger Magoulas recently sat down with Rob Thomas and Tim O’Reilly to discuss Thomas’s AI framework called the AI Ladder, which, according to his recent paper , is a framework that describes “the increasing levels of analytic sophistication that lead to, and buttress, a thriving AI environment.” Thomas notes both in his paper and in a recent keynote discussion he had with O’Reilly that “there is no AI without IA [information architecture].

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The 4 fastest ways not to get hired as a data scientist

KDnuggets

Ready to try to get hired as a data scientist for the first time? Avoiding these common mistakes won’t guarantee an offer, but not avoiding them is a sure fire way for your application to be tossed into the trash bin.

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The difference between DataOps and DevOps and other emerging technology practices.

IBM Big Data Hub

The expectation to achieve faster results continues to rise. Businesses everywhere are looking for ways to improve their operational efficiency and effectiveness to enable the best decision-making. The need to optimize typically comes to a head with the reality that there are many silos within any company.

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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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Automatic Text Summarization in a Nutshell

KDnuggets

Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about Automatic Text Summarization and the various ways it is used.

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6 steps to start your DataOps practice

IBM Big Data Hub

DataOps is the orchestration of people, process, and technology to accelerate the quick delivery of high-quality data to data citizens. When done right, DataOps creates business value because users know what data they have, can trust the quality and its meaning, and use it without violating compliance or privacy laws.

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Data Management and Industry: How Data Influences Decisions

Data Science 101

Following the creation and massive popularity of the internet and all things digital, it became clear to many that data was soon to be the way of the future. Historically, our use of data could provide us with information that would influence decisions but required extensive work to collect, track, and interpret. With the introduction to modern digital data during the 21st century, the power of our computers and technology has broadened the accessibility of data collection, tracking, and interpr

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Implementing DataOps across a banking enterprise

IBM Big Data Hub

Imagine a day in the life of Sarah, a hypothetical Chief Data Officer at a major bank in South Africa. There are many expectations on her shoulders. She struggles to deliver business-ready data to fuel her organization and support the decision makers within the bank. It is her job to put in place a team that will make sense of the myriad of data sources and different representations of data, multiple formats and technologies used to store and move that data.

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Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released

KDnuggets

Ontotext Platform 3.0 features significant technology improvements to enable simpler and faster graph navigation, including GraphQL interfaces to make it easier for application developers to access knowledge graphs without tedious development of back-end APIs or complex SPARQL.

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What is DataOps?

IBM Big Data Hub

Most businesses collect data but are unable to use it to generate business value or deliver insights in a timely fashion. Data volume and data types continue to grow, as do the different types of data citizens—ranging from business users to data scientists. As a result, data management and delivery often become critical bottlenecks. Enter DataOps.

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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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AI the Perfect Solution to the Identity Fraud Epidemic

Smart Data Collective

Fraud has been an ongoing problem for quite some time now. Our technology may have become more sophisticated but so are criminals. It feels more secure now that we have several modes of verification but it’s still unsettling to see news of big companies like Facebook or Yahoo getting their data compromised. Fraud is not a small problem. The global cost of it is $4.2 trillion.

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Components of the DataOps toolchain and best practices to make it successful

IBM Big Data Hub

High-quality data is the core requirement for any successful, business-critical analytics project. It is the key to unlock and generate business value and deliver insights in a timely fashion. However, stakeholders across the board are responsible for data delivery, quickly evolving requirements, and processes. Their preference towards technology is deflating traditional methods of responding to inconsistent data and consequently disappointing users.

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SSIS Layout Formatting Options

Tim Mitchell

Most folks I know go to one extreme or the other when it comes to the visual layout of SQL Server Integration Services packages: either they don’t care a tiny bit about the appearance, or they insist on an easy-to-read layout before a project is considered complete. I am definitely in the second group, and will almost always spend the. The post SSIS Layout Formatting Options appeared first on Tim Mitchell.

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Dashboards Everywhere and Along Comes Squirrel

Paul Blogs on BI

In just the last three days I received three fascinating dashboards. The first was from Microsoft, called MyAnalytics, showing my work habits for the last week based on my Microsoft Outlook usage. It showed I had spent almost 80% of my time in email activities and 20% in meetings (not a normal week for me). It also showed the people I was in contact the most during that week and it tiered them in groups based on amount of interactions.

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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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insightsoftware Builds on Jet Global Deal with Acquisition of Three Jet Solutions Providers in Singapore, New Zealand, and the Netherlands

Jet Global

Deals strengthen global partner network and expand Jet solutions expertise and distribution to reach more customers worldwide. . RALEIGH, N.C. – December 18, 2019 – insightsoftware , the global leader in enterprise resource planning (ERP) and enterprise performance management (EPM) reporting solutions, today announced the acquisition of three authorized distributors of Jet reporting and analytics solutions for Microsoft Dynamics: Dynamic BI Asia, based in Singapore; The Analytics Company, based

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3 Critical Business Technology Trends for 2020

CDW Research Hub

It’s the most wonderful time of the year—a time for celebrating, for looking back on where you’ve been, and looking ahead to what’s next. A big part of evaluating what’s next for your business or organization is staying abreast of new trends and adopting those that make sense for you, especially where business technology is concerned. What are the biggest emerging technology trends and how will they change the way you do business?

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The ravages of concept drift in stream learning applications and how to deal with it

KDnuggets

Stream data processing has gained progressive momentum with the arriving of new stream applications and big data scenarios. These streams of data evolve generally over time and may be occasionally affected by a change (concept drift). How to handle this change by using detection and adaptation mechanisms is crucial in many real-world systems.

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Keeping a Lid on Concurrency within the Vantage Platform

Teradata

Carrie Ballinger discusses the techniques for managing concurrency inside the Advanced SQL Engine and the benefits provided. Read more.

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Reimagined: Building Products with Generative AI

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.

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KDnuggets™ News 19:n48, Dec 18: Build Pipelines with Pandas Using pdpipe; AI, Analytics, ML, DS, Technology Main Developments, Key Trends; Poll on AutoML

KDnuggets

Build Pipelines with Pandas Using pdpipe; AI, Analytics, ML, DS, Technology Main Developments, Key Trends; New Poll: Does AutoML work? Ultralearn Data Science; Python Dictionary How-To; Top stories of 2019 and more.

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A Quick Introduction to Vanilla Neural Networks

Insight

Get the theory behind neural networks straight once and for all! A 2-layer “vanilla” Neural Network. Lauren Holzbauer was an Insight Fellow in Summer 2018. In my last post , we went back to the year 1943, tracking neural network research from the McCulloch & Pitts paper , “ A Logical Calculus of Ideas Immanent in Nervous Activity ” to 2012, when “ AlexNet ” became the first CNN architecture to win the ILSVRC.

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Create Custom Embedded Analytic Visuals with the Sisense Adobe XD Plugin

Sisense

Blog. There’s always something brewing here. Sisense News is your home for new Sisense features, add-ons, and everything else we roll out to empower our users to get the most out of their data. A love story between Sisense BloX and Adobe XD. Big news for analytic app builders looking to make their visuals even more compelling: Sisense has an Adobe XD plugin that lets them create custom visualizations for their Sisense BloX widgets with zero code.

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Three Steps to Boost Your Deployment Score

Decision Management Solutions

As we approach the end of the year, our friends over at the International Institute for Analytics (IIA) are re-tweeting some of their best content. One post in particular caught our eye – What’s Your Deployment Score? This is a great piece by Tom Davenport (who wrote a foreword for my new book Digital Decisioning: Using Decision Management to Deliver Business Impact from AI ) about deployment: Great data and fantastic models have no impact on the world unless they are deployed into operati

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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.