Thu.Dec 19, 2019

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Interpretability part 3: LIME and SHAP

KDnuggets

The third part in a series on leveraging techniques to take a look inside the black box of AI, this guide considers methods that try to explain each prediction instead of establishing a global explanation.

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How Do Super Rookies Start Learning Data Analysis?

FineReport

For super rookies, the first task is to understand what data analysis is. Data analysis is a type of knowledge discovery that gains insights from data and drives business decisions. From Google. There are two points here. One is how to gain insights from the data. Data is cold and can’t speak. Professional data analysts must have a wealth of business knowledge in order to know from the data what has happened and what is about to happen.

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Alternative Cloud Hosted Data Science Environments

KDnuggets

Over the years new alternative providers have risen to provided a solitary data science environment hosted on the cloud for data scientist to analyze, host and share their work.

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The Most Popular Data and Analytics Research in 2019

Andrew White

The year is almost up and though there is only a couple of weeks left, the enthusiasm that drives folks to gartner.com and access our research is slowing down. I can’t think why! Maybe it’s something to do with the holidays? Well, it’s time to give you a summary of the years’ most popular research in data and analytics. I exclude our branded notes as they are always very popular.

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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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5 Ways to Apply Ethics to AI

KDnuggets

Here are six more lessons based on real life examples that I think we should all remember as people working in machine learning, whether you’re a researcher, engineer, or a decision-maker.

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Top 7 Data Governance and Metadata Management Blog Posts of 2019

erwin

Data has been the driving force of the decade. Digital pioneers like Amazon, Netflix and Uber account for some of the most extreme market disruption their respective industries have faced. But such success cannot be attributed soley to head-starts. Many organizations have tried and failed to become truly “data-driven,” and many organizations will continue to do so.

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Reflecting on the Past Decade in Analytics

DataRobot Blog

by Jen Underwood. 2010. What was hot and what was not? From what I can remember, in-memory analytics, mobile BI, OLAP cubes and easier to use drag-and-drop analytics tools got all the buzz. Read More.

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Reality and misconceptions about big data analytics, data lakes and the future of AI

IBM Big Data Hub

With the amount of choices surrounding big data analytics, data lakes and AI, it can sometimes be difficult to tell fact from fiction. With more than 40% of organizations expecting AI to be a “game changer,” it’s important to have a complete picture of the capabilities and opportunities available.

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A Better Way to Report Financials on NetSuite

Jet Global

As one of the first cloud-based ERPs, Oracle’s NetSuite introduced a modern and efficient way to manage operational and financial data. This advance had a significant effect on improving business cycles and easily delivering information to more users. In each department, teams found NetSuite easy to access and use. However, one department was beginning to feel some pain: some reporting pain.

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One-Click Package Restart in SSDT

Tim Mitchell

This quick tip is likely to be the most brief of the entire collection, but is also one of the most practical. When testing SSIS packages during development in SQL Server Data Tools, it’s very common to run and re-run the same package numerous times. It’s fairly easy to stop and restart the package each time using the Stop and. The post One-Click Package Restart in SSDT appeared first on Tim Mitchell.

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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.

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Small Business Gets Big Data Benefits with 3 Data Sources

ScienceSoft

Find out what data sources your small business can use to benefit from the powers of big data analytics.

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ALMA Observatory: Building a Revolutionary Data Science Culture

Dataiku

Every astronomer knows the critical importance of good data, but few observatories have recognized the importance of applying good data science to their operations.

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Aligning Data Virtualization, Streaming, and ETL

Data Virtualization

What do data virtualization, streaming, and extract, transform, and load (ETL) processes have in common? They all deliver data from disparate sources to the business intelligence (BI), analytics, and other applications used by businesspeople, data scientists, and analysts.

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AI And Data: A Pain Or Gain? Here’s What The Future Looks Like

Smart Data Collective

Yes, it’s AI again! Artificial Intelligence (AI) is always in the limelight from the last couple of years. Mostly it is considered as a blessing to the IT world. However, many experts have shown their doubtfulness too. No, you just can’t say “Ok Boomer” here! Of course, they have greater reasons i.e. a threat to data security. So, AI is on whose side?

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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.