Sat.Feb 15, 2020 - Fri.Feb 21, 2020

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There is No Noise?—?Only Bias

Insight

There is No Noise?—?Only Bias Understanding why noise in machine learning is nothing but bias In this post, we explain how bias and noise in machine learning are two sides of the same coin. God does not play dice.?—?Albert Einstein Einstein famously gave this statement in reaction to the emerging theory of quantum mechanics, which seemed to defeat the fundamental laws of physics.

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Differences Between ‘Available’ and ‘Accessible’

TDAN

A few months back, our company enjoyed a retreat a few hours north of the city. We bonded, brainstormed, and set visions and goals for the development of our company and our products. We also had bonfires with s’mores, and that’s more relevant than you might think. We ended up with a surplus of marshmallows […].

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Top Machine Learning Algorithms: How They Work (In Plain English)

Dataiku

This series will go over at a high level what machine learning is plus take a deeper dive into some of the top algorithms and how they work — in plain English!

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CNN vs. RNN vs. MLP – Analyzing 3 Types of Neural Networks in Deep Learning

Analytics Vidhya

Overview Check out 3 different types of neural networks in deep learning Understand when to use which type of neural network for solving a. The post CNN vs. RNN vs. MLP – Analyzing 3 Types of Neural Networks in Deep Learning appeared first on Analytics Vidhya.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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5 key areas for tech leaders to watch in 2020

O'Reilly on Data

O’Reilly online learning contains information about the trends, topics, and issues tech leaders need to watch and explore. It’s also the data source for our annual usage study, which examines the most-used topics and the top search terms. [1]. This combination of usage and search affords a contextual view that encompasses not only the tools, techniques, and technologies that members are actively using, but also the areas they’re gathering information about.

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Data in 2020: Ventana Research Agenda

David Menninger's Analyst Perspectives

Ventana Research recently announced its 2020 research agenda for data, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value and improve business outcomes. Data volumes continue to grow while data latency requirements continue to shrink. Meanwhile, virtually every organization is confronting a need for good data governance.

More Trending

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Learn Image Classification on 3 Datasets using Convolutional Neural Networks (CNN)

Analytics Vidhya

Introduction Convolutional neural networks (CNN) – the concept behind recent breakthroughs and developments in deep learning. CNNs have broken the mold and ascended the. The post Learn Image Classification on 3 Datasets using Convolutional Neural Networks (CNN) appeared first on Analytics Vidhya.

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15 Examples Of Financial Graphs And Charts You Can Use For Your Business

datapine

The financial health, flow, and fluidity of your business will ultimately dictate its long-term success, which is why monitoring your money matters carefully, comprehensively, and accurately is absolutely essential. In our data-driven digital age, ‘business intelligent’ organizations with the ability to collate, organize, and leverage the insights that are most valuable to their ongoing commercial goals are the ones that are destined to thrive in the long-term.

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Analytics in 2020: Ventana Research Agenda

David Menninger's Analyst Perspectives

Ventana Research recently announced its 2020 research agenda for analytics , continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value from their technology investments and improve business outcomes. It’s been exciting to follow the emergence of innovative capabilities in the analytics market, but for businesses it can be challenging to stay on top of all these changes.

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Scoring Goals with Data: Champions League Predictions

DataRobot

We at DataRobot have been enjoying building models to predict various sporting events around the world. However, it’s been pointed out to me that we have shown a bias for covering North American events so far. Several colleagues in Europe asked when we were going to predict the world’s most popular game, football. So I enlisted Chloe and Akshay to help me and see if we could predict the Champions League Knockout Stage and the eventual Champions League winner.

Modeling 128
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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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MongoDB in Python Tutorial for Beginners (using PyMongo)

Analytics Vidhya

Overview MongoDB is a popular unstructured database that data scientists should be aware of We will discuss how you can work with a MongoDB. The post MongoDB in Python Tutorial for Beginners (using PyMongo) appeared first on Analytics Vidhya.

Analytics 397
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Enterprise Architecture and Business Process Modeling Tools Have Evolved

erwin

Enterprise architecture (EA) and business process (BP) modeling tools are evolving at a rapid pace. They are being employed more strategically across the wider organization to transform some of business’s most important value streams. Recently, Glassdoor named enterprise architecture the top tech job in the UK , indicating its increasing importance to the enterprise in the tech and data-driven world.

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Data Management 20/20: The Trinity of the Business Glossary

TDAN

Essential Components forthe Business/IT Lexicographer Today’s organizations often struggle with how poorly their information systems perform. Sources of this poor performance can be many, including functions and components in the conceptual, structural, organizational, and operational domains, among others. One recurring source of this poor performance is linguistic in origin.

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How Big Data Has Changed the Financial Industry

Smart Data Collective

The accessibility and value of consumer data has grown substantially in the past several years. These days, nearly every company bigger than a “mom and pop” shop works to gather and analyze terabytes of data from their customers, hoping to better understand and serve them while one-upping the competition. In the financial industry, these efforts are particularly intense.

Big Data 120
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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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5 Useful Tools To Provide Effective Data Visualization For Translators

Analytics Vidhya

Introduction Language translators are in a world of their own. Our task involves meticulous preparation and quality checks before the final touches are put. The post 5 Useful Tools To Provide Effective Data Visualization For Translators appeared first on Analytics Vidhya.

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A Real-Life Excel Test from a Job Interview: Can You Pass??

Depict Data Studio

My heart just about stopped. …. Ten years ago, I was interviewing for an analyst position. The official job title was “Learning and Evaluation Specialist.” Nowadays, you might hear it called “Quality Improvement Specialist,” “Research Analyst,” or even “Data Scientist.”. I remember sitting in the interviewer’s office. He was asking me about my Excel skills.

Testing 118
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Cloud Data Science 7

Data Science 101

Welcome to Cloud Data Science 7. Announcements around an exciting new open-source deep learning library, a new data challenge and more. News. Microsoft Releases DeepSpeed for Training very large Models DeepSpeed is a new open-source library for deep learning optimization. Using a component of the library named ZeRO, it can train models with up to 100 billion parameters.

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Navigating Your Career in Electrical Engineering in the Big Data Era

Smart Data Collective

Many careers have been heavily impacted by changes in big data. The big data revolution has had a profound effect on healthcare, marketing and many other fields. One of the fields that has been most affected by big data is electrical engineering. Tom Dietterich, a professor of the Department of Electrical Engineering and Computer Science at Portland State University, has written an article on the impact of big data in this field.

Big Data 114
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Marketing Operations in 2025: A New Framework for Success

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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11 Powerful Talks from rstudio::conf 2020 you Must Watch – A Treat for R Users!

Analytics Vidhya

Introduction to the rstudio::conf 2020! I’m a heavy R user. It was the first programming language I learned (thanks to my interest in data. The post 11 Powerful Talks from rstudio::conf 2020 you Must Watch – A Treat for R Users! appeared first on Analytics Vidhya.

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Ron Lewis makes retail sense with analytics

IBM Big Data Hub

This story is part of Analytics Heroes , a series of profiles on leaders transforming the future of business analytics.

Analytics 133
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Dataiku: A Gartner Magic Quadrant Leader in Data Science and Machine-Learning Platforms

Dataiku

Our 2019 ended with a bang with the announcement that Dataiku became a unicorn valued at $1.4 billion and gained a new investor (CapitalG). On top of all of that excitement, we’re thrilled to kick off the year by being named a Leader in the Gartner 2020 Magic Quadrant for Data Science and Machine-Learning Platforms!

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5 Ways Big Data Has Revolutionized Invoicing Software

Smart Data Collective

Big data is changing the nature of invoicing software in many ways. In 2015, Spend Matters wrote a detailed report on the applications of big data in the e-invoicing industry. This has changed the perception business owners had of invoicing applications, because they often ignored the benefits of it before then. Big Data Transforms Invoicing Software Applications.

Big Data 112
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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

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Top 3 Winning Solutions and Approaches from LTFS Data Science FinHack 2 (with Code)

Analytics Vidhya

Overview Presenting the top three winning solutions and approaches from the LTFS Data Science FinHack 2 The problem statement for this hackathon was from. The post Top 3 Winning Solutions and Approaches from LTFS Data Science FinHack 2 (with Code) appeared first on Analytics Vidhya.

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And Now for Something Completely Different

Juice Analytics

via GIPHY Your choices for visualizing and communicating data are a bit of a mixed blessing: There are low-code ways to build interactive analytical apps. For example, R Shiny is great if you're a data scientist who loves R — but not so good if you’re non-technical. You can use no-code tools to create beautiful visualizations. I'm impressed with Flourish's beautiful collection of embeddable visualizations — but stand-alone visualizations are limiting.

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Naive Bayes Sentiment Analysis in Python After Preparing Data Using SQL

Sisense

Analytics is constantly evolving; as datasets become bigger and more complex, only AI, materialized views, and more sophisticated coding languages will be able to glean insights from them. In Next-Level Moves , we dig into the ways advanced analytics are paving the way for the next wave of innovation. Machine learning (ML) refers to the use of existing data, computing power, and effective algorithms to identify patterns in data, recognize those patterns when they occur again, and correctly predi

Testing 93
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Cloud And Big Data Technology Are Disrupting Injection Molding

Smart Data Collective

Injection molding is vital to the mass production of plastics and plastic products. Due to the variety of complications with mold design and mold manufacturing, and the combining of plastics and molding machines, there is difficulty in molding products with high quality and precision. However, Big Data and Cloud technology make the process simpler and improve quality.

Big Data 104
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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Gartner’s 2020 Magic Quadrant for Data Science and Machine Learning Tools – check out the new Leaders!

Analytics Vidhya

Which Data Science or Machine Learning Tool is the Best? We are living in the age of choices. The data revolution has transformed the. The post Gartner’s 2020 Magic Quadrant for Data Science and Machine Learning Tools – check out the new Leaders! appeared first on Analytics Vidhya.

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Logarithms Unmuddled

Perceptual Edge

I often write about topics that I myself have struggled to understand. If I’ve struggled, I assume that many others have struggled as well. Over the years, I’ve found several mathematical concepts confusing, not because I’m mathematically disinclined or disinterested, but because my formal training in mathematics was rather limited and, in some cases, poorly taught.

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How in-line address data quality delivers business ready data for AI initiatives

IBM Big Data Hub

Imagine opening your mailbox and seeing a letter addressed to “current resident,” or having your financial institution’s AI powered digital assistant inform you that your replacement card is on its way to your old address.

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Information Systems Careers Are the New Frontier of Big Data

Smart Data Collective

Are you looking to capitalize off of your knowledge of big data? There are a lot of careers that talented data scientists can pursue. Information systems careers are among the most promising. IBM Big Data and Analytics Hub has talked about some of the biggest changes impacting the world of big data. They found an interesting quandary that many companies are facing.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.