Fri.Nov 22, 2019

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Advice for New and Junior Data Scientists

KDnuggets

If you are a new Data Scientists early in your professional journey, and you’re a bit confused and lost, then follow this advice to figure out how to best contribute to your company.

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Feed your data lake with change data capture for real-time integration and analytics

IBM Big Data Hub

Haruto Sakamoto, the Chief Information Officer at a Japanese multinational imaging company, had a few challenges to contend with. His business units had a presence in 180 countries worldwide with geographically-dispersed data warehouses and business intelligence applications in various locations.

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Automated Machine Learning Project Implementation Complexities

KDnuggets

To demonstrate the implementation complexity differences along the AutoML highway, let's have a look at how 3 specific software projects approach the implementation of just such an AutoML "solution," namely Keras Tuner, AutoKeras, and automl-gs.

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IBM Cloud Pak for Data ready to support DataOps’ practices

IBM Big Data Hub

The number of business segments requiring data to drive contextual insights is increasing. Leaders are seeking new ways to manage the pressures of delivering high-quality data faster across their businesses. To date, many of these projects have focused solely on ingesting data into a data lake which has led to repositories of uncleansed and ungoverned data.

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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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Text Encoding: A Review

KDnuggets

We will focus here exactly on that part of the analysis that transforms words into numbers and texts into number vectors: text encoding.

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A picture worth a thousand volts

IBM Big Data Hub

Learn how marine solution provider James Fisher and Sons plc and the IBM Data Science and AI Elite team surge towards a renewable tomorrow with the electrifying power of data visualization built on IBM Watson Studio.

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A Message For Your Business: How to Become Data Literate!

Smarten

Why is Data Literacy Important? If you have attended technology conferences or read industry publications, you have probably heard the term ‘Data Literacy’. If your enterprise is considering undertaking an initiative to encourage and nurture data literacy in your organization, you may be looking for a better understanding of the concept and the benefits.

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Secure Your IoT Data With a Zero-Trust Strategy

CDW Research Hub

If you’ve felt like new reports of data hacks and security breaches are becoming more common, it’s not your imagination. The rise of the Internet of Things (IoT) as one of the fastest-growing device categories today means that securing your IoT data is more important—and difficult—than ever. By some estimates, as many as 300 billion devices will be connected within the next 10 years, and as that number grows, IoT security concerns will intensify as well.

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Why Cloud-Native Management Tools Aren’t Enough

Nutanix

Keeping track of various and sundry cross-cloud resources has the potential to become mind-numbingly complex as hybrid and multi-cloud deployments heat up.

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How Content Personalization is Driving the AI Disruption in Media

Dataiku

In a world of increasingly digital and personalized experiences, consumers are embracing the ever-expanding opportunities to enjoy media and entertainment products uniquely tailored to their own preferences, contexts and schedules.

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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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Why Cloud-Native Management Tools Aren’t Enough

Nutanix

Keeping track of various and sundry cross-cloud resources has the potential to become mind-numbingly complex as hybrid and multi-cloud deployments heat up.

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The Complexity of AI Bias: A Look at the Apple Card

DataRobot

The recent uproar surrounding the credit scoring algorithm employed by the Apple Card presents an opportunity to review the manifold types of biases that can affect AI algorithms, the possible consequences of neglecting such biases, and the best practices for allowing companies to develop processes to ensure that AI bias problems are adequately addressed.

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Big Data Yields Important Insights On Student Loan Forgiveness

Smart Data Collective

Big data is transforming many facets of our lives. One of the ways consumers are looking to big data is with the student loan crisis. Big data advances could also make the government more understanding with its student loan forgiveness program. Big Data Could Turn the Student Loan Crisis on its Head. There are multiple applications of big data for solving the student loan crisis.

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Cloud Data Science News – Beta #3

Data Science 101

Here are this week’s news and announcements related to Cloud Data Science. Plus, there are some links for Videos and Tutorials. Announcements. Google Introduces Explainable AI Many industries require a level of interpretability for their machine learning models. Black box solutions are not always ok. Google is launching Explainable AI which quantifies the impact of the various factors of the data as well as the existing limitations.

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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.