Sat.Apr 11, 2020 - Fri.Apr 17, 2020

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Everything you Should Know about Confusion Matrix for Machine Learning

Analytics Vidhya

Confusion Matrix – Not So Confusing! Have you been in a situation where you expected your machine learning model to perform really well but. The post Everything you Should Know about Confusion Matrix for Machine Learning appeared first on Analytics Vidhya.

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APIs to Track COVID-19

Dataconomy

Editor’s Note: The article was originally published by Wendell Santos, the editor at ProgrammableWeb.com. Check back there as the article will continue to be updated as new APIs related to COVID-19 are made available. Over the past two months, as COVID-19 has proliferated, ProgrammableWeb has been tracking APIs that provide access to data related.

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The Growing Importance Of Data Collection For Customer Service

Smart Data Collective

Big data is crucial for any organization that wants to attract and retain customers. A study by McKinsey Global Institute found that data-driven companies are 400% more likely to retain customers and 2,200% more likely to acquire new ones. Back in 2011, my colleagues and I first started discussing the evolving standards of customer service in business.

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Commando, Soldier, Police and Your Career Choices

Eugene Yan

Should I join a start-up? Which offer should I accept? A simple metaphor to guide your decisions.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Exception Handling in Python – Get Rid of those Errors!

Analytics Vidhya

Introduction Errors are the bane of a programmer’s existence. You write an awesome piece of code, are ready to execute it and build a. The post Exception Handling in Python – Get Rid of those Errors! appeared first on Analytics Vidhya.

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How healthcare institutions and hackers cooperate

Dataconomy

Hacking Health Berlin, Charité University Hospital Berlin, the Berlin Institute of Health, Data Natives and Vision Health Pioneers brought together 164 participants, and 20 hacking teams that produced 14 community-sourced tech solutions to meet the COVID-19-related needs of Germany’s leading clinicians and researchers. Let’s take a look at the results.

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How to Give a Kick-Ass Data Science Talk

Eugene Yan

Why you should give a talk and some tips from five years of speaking and hosting meet-ups.

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10 Productive Jupyter Notebook Hacks, Tips and Tricks!

Analytics Vidhya

Overview Jupyter notebooks are a great tool for data scientists but we can make them even better using these hacks, tips, and tricks We. The post 10 Productive Jupyter Notebook Hacks, Tips and Tricks! appeared first on Analytics Vidhya.

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Protected: How community-sourced tech targets coronavirus in Greece

Dataconomy

There is no excerpt because this is a protected post. The post Protected: How community-sourced tech targets coronavirus in Greece appeared first on Dataconomy.

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Big Data Options Spark Confusion On Web Design Options For SMEs

Smart Data Collective

Big data is streamlining the web design process. Companies have started leveraging big data tools to create higher quality designs, personalize content and ensure their websites are resilient against cyberattacks. Last summer, Big Data Analytics News discussed the benefits of using big data in web design. Many of the benefits of big data are outstanding.

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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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Moving from Red AI to Green AI, Part 1: How to Save the Environment and Reduce Your Hardware Costs

DataRobot

Machine learning, and especially deep learning, has become increasingly more accurate in the past few years. This has improved our lives in ways we couldn't imagine just a few years ago, but we're far from the end of this AI revolution. Cars are driving themselves, x-ray photos are being analyzed automatically , and in this pandemic age, machine learning is being used to predict outbreaks of the disease , help with diagnosis, and make other critical healthcare decisions.

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How to Generate Random Numbers in Python?

Analytics Vidhya

The world is governed by chance. Randomness stalks us every day of our lives. . The post How to Generate Random Numbers in Python? appeared first on Analytics Vidhya.

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How startup collaborations are boosting the Ruhr region

Dataconomy

Corporations need to digitalize in order to overcome their challenges. That’s especially true for the large industrial corporations in Germany’s Ruhr region and its over 50 cities and municipalities. By collaborating with startups, they are able to drive the change forward, and that’s what the Data Hub program by Gründerallianz. The post How startup collaborations are boosting the Ruhr region appeared first on Dataconomy.

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3 Reasons Landlords Should Reconsider Selling Tenant Data to Marketers

Smart Data Collective

Data is for sale on just about every corner of the internet. Social media platforms have openly acknowledged selling user data and activities to marketers. That same data is freely available to marketers utilizing PPC ad campaigns. Businesses can launch ads to target the usual demographics, but they can also target users who have visited specific websites, joined certain groups, and “liked” specific interests.

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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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ML Ops: Your Path to Fully Embracing AI

DataRobot

According to a recent survey by NewVantage Partners, only 15% of leading enterprises have deployed AI into widespread production. Why so few? For organizations to overcome the hurdles of deploying and managing AI, they have to overcome several major hurdles around model deployment, management, and monitoring, in addition to bridging the gap between IT and data science teams.

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Getting Started with Community Detection in Graphs and Networks

Analytics Vidhya

Introduction The word “community” has entered mainstream conversations around the world this year thanks in no large part to the ongoing coronavirus pandemic. Given. The post Getting Started with Community Detection in Graphs and Networks appeared first on Analytics Vidhya.

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Three Steps to Using Sensitive Data for Facilitating M&A Scenarios

Dataconomy

In 2020, companies face an operational environment that is unlike any seen before. Rapid globalization has created fierce competition, and digitalization is driving innovation in every direction. As a result, firms that fall behind are going out of business, and more than half of all Fortune 500 companies have left. The post Three Steps to Using Sensitive Data for Facilitating M&A Scenarios appeared first on Dataconomy.

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Avoid Data-Driven Cyber Attacks By Avoiding These 5 File Sharing Errors

Smart Data Collective

File sharing habits that can cripple your business. Big data has made cyberattacks more frightening than ever. A growing number of hackers have started using big data to orchestrate new cyberattacks, which can be incredibly damaging. You need to be aware of the risks of security breaches in the age of big data. You should avoid common mistakes that hackers can exploit with machine learning tools in their arsenal of weapons.

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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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Join DataRobot at ODSC Virtual

DataRobot

While the world is going through these turbulent times , AI remains a key focus for many organizations that are trying to solve emerging social and economic problems. ODSC has always been an exceptional place to highlight these solutions and share some of the thought leadership around AI and machine learning, which is why we are excited to be a part of ODSC Virtual Conference & Expo this week.

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HCI & vSAN with VMWare's Lee Caswell

DataCentric podcast

HCI has become a rare success story, a technology that continues to grow at 25-30% year-over-year. There isn't a technology company doing more to fuel that growth than VMware, with its leading vSAN solution. vSAN almost defines HCI, owning nearly 40% of the all HCI installations (with Nutanix hot on its heels with 27% of the market). The face of vSAN for VMware is Lee Caswell, and this week Lee joins Matt & Steve to talk about what's behind the growth of HCI as a technology, what'

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Becoming A Data Scientist In 2020: Skills, Degrees, And Work Experience

Smart Data Collective

The future of data science jobs continues to be brighter than ever in 2020. Why? According to Glassdoor’s list of Best Jobs in America for the past four years, “data scientist” topped in terms of job demand, job satisfaction, and pay with an average base salary of more than $100,000 per year. So, who are the present-day data scientists and what does it take to become one?