Thu.Sep 29, 2022

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The Top Three Entangled Trends in Data Architectures: Data Mesh, Data Fabric, and Hybrid Architectures

Cloudera

Data teams have the impossible task of delivering everything (data and workloads) everywhere (on premise and in all clouds) all at once (with little to no latency). They are being bombarded with literature about seemingly independent new trends like data mesh and data fabric while dealing with the reality of having to work with hybrid architectures.

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Concept of Cryptography in Blockchain

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Cryptography is a way of securing data against unauthorized access. In the blockchain, cryptography is used to secure transactions between two nodes in the blockchain network. As mentioned above, there are two main concepts in blockchain cryptography and hashing. Cryptography encrypts messages in […].

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

Table of Contents. 1) What Is Data Quality Management? 2) Why Do You Need DQM? 3) The 5 Pillars of DQM. 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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Dummies Guide to Writing a Custom Loss Function in Tensorflow

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Have you ever encountered a situation where you felt to use a custom loss function in your machine learning model? Maybe, you had to experiment with a new loss function while writing a research paper or to handle a new business case. […]. The post Dummies Guide to Writing a Custom Loss Function in Tensorflow appeared first on Analytics Vidhya.

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Beyond the Basics of A/B Tests: Innovative Experimentation Tactics You Need to Know as a Data or Product Professional

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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Welcome to TensorFlow!

KDnuggets

TensorFlow in Action teaches you to construct, train, and deploy deep learning models using TensorFlow 2. In this practical tutorial, you’ll build reusable skills hands-on as you create production-ready applications.

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Can Voice Conversion Improve ASR in Low-Resource Settings?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: Canva Introduction Voice conversion (VC) can be used to improve the performance of speech recognition systems in low-resource languages by augmenting limited training data. However, VC has not been extensively used for this task considering the practical issues like compute speed and […].

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Let’s Discuss the Web 2.0 and Web 3.0

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Overview The WWW is often used for application. The programmatic available interfaces are referred to as “web services.” In today’s era, Most people cannot envisage life without the internet. The global has transformed into a web of data. The semantic wave enclasps three stages […].

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Data-Driven Companies Leverage OCR for Optimal Data Quality

Smart Data Collective

OCR is the latest new technology that data-driven companies are leveraging to extract data more effectively. There are a number of benefits of using it to your company’s advantage. OCR and Other Data Extraction Tools Have Promising ROIs for Brands. Big data is changing the state of modern business. A growing number of companies have leveraged big data to cut costs, improve customer engagement, have better compliance rates and earn solid brand reputations.

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How to Classify the Images of the Cifar-10 Dataset using CNN?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In today’s world, the demand for machine learning and artificial intelligence is increasing, with more companies developing computer systems and building new technologies to achieve this goal. AI has become the world’s fastest-growing technology, with an estimated total of over 30,000 new […].

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Data-Driven Marketers Must Configure Outlook Data Files

Smart Data Collective

Big data has changed the marketing profession in extraordinary ways. Global companies spent over $3.2 billion on marketing analytics software last year. This figure is expected to grow in the future. There are many different ways that marketers can leverage data analytics to create successful marketing strategies. One of the biggest benefits is in the realm of email marketing.

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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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Importance of Skewness, Kurtosis, Co-efficient of Variation

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Why is a clearer understanding of skewness, kurtosis, and coefficient of variation needed for better decision-making based on their significance in a specific domain? Within what range of skewness and kurtosis a distribution shall be considered normal before selecting appropriate Statistical Tests (Hypothesis […].

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How universities can accelerate their digital transformations

CIO Business Intelligence

University leaders have long understood that the future is digital, but thereâ??s now added urgency to modernise. The pandemic is in part the cause â?? highlighting that true business resilience and digital transformation are inseparable. But there are longer-term factors at play too, including the expectations of digitally native students and the requirement to provide them with work-ready skills.

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AI Technology Helps App Marketplaces Compete with App Store

Smart Data Collective

AI has become one of the most important gamechangers for businesses and customers relying on mobile technology. This is one of the reasons companies are spending over $328 billion on AI technology. One of the many reasons that AI is changing the landscape of mobile technology is that it helps develop and distribute apps more easily than ever. We previously talked about some of the ways that AI is making it easier to develop new mobile apps.

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An expanded attack surface: The cybersecurity challenges of managing a hybrid workforce

CIO Business Intelligence

With the global pandemic upending the traditional way we work, employees across every market sector in New Zealand are now spending their workdays alternating between offices, their homes and other locations. It’s a hybrid work model that Kiwis have embraced and it is here to stay. At a recent CIO New Zealand roundtable event in Auckland, supported by Palo Alto Networks and Vodafone New Zealand, senior technology executives from organisations across Aotearoa discussed the challenge of keeping se

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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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Top 5 Machine Learning Practices Recommended by Experts

KDnuggets

this article is intended to help beginners improve their model structure by listing the best practices recommended by machine learning experts.

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Balancing Healthcare AI Innovation with Governance | Domino Data Lab

Domino Data Lab

By David Schulman , Head of Partner Marketing , and Caroline Phares , Global Head of Health and Life Sciences. From early disease detection to intelligent clinical trial designs to personalized medicine, the promise of AI/ML in healthcare and life sciences is great, with “more than 57% of healthcare and life sciences organizations rating AI/ML important or very important, ” according to Ventana Research in their recent white paper Top AI Considerations for Chief Data and Analytics Executives.

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A Day in the Life of a Data Scientist: Expert vs. Beginner

KDnuggets

Let’s learn more about what a Data Scientist gets up to.

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12 fastest growing US cities for IT talent

CIO Business Intelligence

These days, it’s difficult to find a company that isn’t looking for qualified professionals to fill vital IT roles. In fact, despite layoffs and hiring freezes reported among technology companies, IT job postings grew month-over-month in the first half of 2022, a boom Dice.com attributes to IT hiring having strengthened in nearly every other industry outside of tech, according to its Tech Jobs Report.

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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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High-Performance, Scalable Array Storage with TensorStore

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Various contemporary computer science and machine learning applications use multidimensional datasets encompassing a single expansive coordinate system. Two examples are utilizing air measurements over a geographical grid to predict the weather or making medical imaging predictions using multi-channel image intensity values from a […].