Thu.Jul 01, 2021

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Data Virtualization and Data Science

Data Virtualization

If we look at a typical , many of its stages have more to do with data than science. Before data scientists can begin their work regarding data science, they often must begin by: Finding the right data Gaining access. The post Data Virtualization and Data Science appeared first on Data Virtualization blog.

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An Ultimate Guide to Opencv-Learning Libraries 1.0

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction “Vision is an Art of Seeing what is invisible to. The post An Ultimate Guide to Opencv-Learning Libraries 1.0 appeared first on Analytics Vidhya.

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DevOps Is Not DataOps

DataKitchen

Arvind Murali, Intelligent Data podcast host, interviews DataKitchen CEO Chris Bergh about how DataOps helps improve the speed of data & analytics deployment. The post DevOps Is Not DataOps first appeared on DataKitchen.

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Perform Logistic Regression with Pytorch Seamlessly

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Regression has numerous applications in real life. Linear regression is used. The post Perform Logistic Regression with Pytorch Seamlessly appeared first on Analytics Vidhya.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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SAS Rated with Assurance in Analytics and Data Value Index

David Menninger's Analyst Perspectives

We are happy to share some insights about SAS drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

Analytics 162
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PyTorch 1.9 – Towards Distributed Training and Scientific Computing

Analytics Vidhya

ArticleVideo Book Overview So what does the newest release of PyTorch, i.e, 1.9 have to offer? Facebook’s PyTorch team has vastly amped up its. The post PyTorch 1.9 – Towards Distributed Training and Scientific Computing appeared first on Analytics Vidhya.

Analytics 319

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Pros and Cons of Buying Cryptocurrency with Blockchain ATMs

Smart Data Collective

Blockchain has played a very important role in the inception of bitcoin and other cryptocurrencies. Blockchain even transformed the traditional financial industry, as around 15% of banks started using it in 2017. Blockchain has also created an unexpected bridge between the cryptocurrency market and traditional financial providers. It has made it possible to start accessing bitcoins the same way people would access regular fiat currencies.

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A New Era for the Intelligent Enterprise, with RISE with SAP

Timo Elliott

My updated, 10-minute summary of the different components of SAP’s Intelligent Enterprise vision, with information on RISE with SAP, a program to help you become one! And there’s a version in French here !

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AI Technology is Invaluable in The Fight Against Ransomware

Smart Data Collective

Artificial intelligence is very important for solving many modern business challenges. One of the most important applications of AI technology is in the context of cybersecurity. Ransomware is a significant threat in our connected world. Whether it’s at your business or on your personal devices, a hacker/attacker can cause untold damage and wreak havoc on your life with a successful ransomware attack.

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How to Build a Winning Data Team

DataCamp

Your organization is generating countless data points, and this data hides many actionable insights that can improve your company’s performance. Learn how to build a winning data-driven team that leverages the right data science skills.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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Lessons Learned Shadowing the Mythical 10x Programmer

Dataiku

In the book “ Mythical Man-Month ,” Fred Brooks demonstrates that the most efficient developers, the so-called “10x developers,” code ten times more efficiently than their average counterparts. Surprisingly enough, the heirs of the Stakhanovite movement are software engineers working for big tech companies.

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Well Architected DRaaS Solutions

Nutanix

Cost, complexity, and lack of expertise remain the primary culprits in determining the right solution for the business, but IT organizations must keep calm and DR on.

IT 35
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How to Create and Maintain Business Value With AI

Dataiku

Organizations are hard-pressed to fine-tune their greater data science and AI strategy based on their learnings from the turbulence of 2020 and its impacts on the business (and, notably, models in production). They are resolute, focused on untapping new ways to bridge the gap between “business value generation” as a buzzword phrase and actually putting it in practice in a way that is collaborative and sustainable for the long term.

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Building a Named Entity Recognition model using a BiLSTM-CRF network

Domino Data Lab

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

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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Nutanix HCI is Now Certified to Run Azure Arc Data Services

Nutanix

Nutanix and Microsoft’s Hybrid Cloud Partnership Adds Azure Arc-enabled Data Services To A Feature-Rich hybrid cloud Kubernetes Stack.

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Building a Named Entity Recognition model using a BiLSTM-CRF network

Domino Data Lab

In this blog post we present the Named Entity Recognition problem and show how a BiLSTM-CRF model can be fitted using a freely available annotated corpus and Keras. The model achieves relatively high accuracy and all data and code is freely available in the article. What is Named Entity Recognition? Named Entity Recognition (NER) is an NLP problem, which involves locating and classifying named entities (people, places, organizations etc.) mentioned in unstructured text.

Modeling 111
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Welcome to the Era of the Augmented Marketer

Sisense

Blog. In a world of rapid technological change, digital tools for marketers are having a moment. Marketing technology tools (also referred to as MarTech tools) have multiplied from about 150 in 2011 to around 8,000 today, a 5,233% increase that sends a clear message: Marketers are embracing digital assistance and data/analytics. The average enterprise now uses 120 cloud-based marketing tools (according to chiefmartec.com); in many companies, marketing departments are the heaviest users of cloud

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5 Ways to Streamline Your Accounting Month-End Close Process

Jet Global

The accounting month-end close process can be stressful for the finance team in many organizations. The pressure is on to get the books closed cleanly, accurately, and without delay. That frequently means some late nights at the office (or these days, in the home office), and a good deal of research and analysis. To streamline your month-end accounting close process , here are some best practices: 1.

Finance 98
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Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.