Sat.Mar 02, 2019 - Fri.Mar 08, 2019

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29 Inspiring Women Blazing a Trail in the Data Science World

Analytics Vidhya

This article has been updated on Women’s Day, 2019. Introduction This women’s day, we at Analytics Vidhya are celebrating the power of women in. The post 29 Inspiring Women Blazing a Trail in the Data Science World appeared first on Analytics Vidhya.

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Lessons learned building natural language processing systems in health care

O'Reilly on Data

NLP systems in health care are hard—they require broad general and medical knowledge, must handle a large variety of inputs, and need to understand context. We’re in an exciting decade for natural language processing (NLP). Computers will get as good as humans in complex tasks like reading comprehension, language translation, and creative writing.

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Domo Continues to Expand Cloud-Based BI and Analytics

David Menninger's Analyst Perspectives

I am happy to share some insight on Domo drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

Analytics 167
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Continuous delivery of data drives continuous intelligence

IBM Big Data Hub

Success with AI models depends on achieving success with collecting and organizing your data, then analyzing the data to make smarter business decisions.

Modeling 103
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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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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11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals)

Analytics Vidhya

Introduction The rapid rise of data science as a professional field has lured in people from all backgrounds. Engineers, computer scientists, marketing and finance. The post 11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals) appeared first on Analytics Vidhya.

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Microsoft Launches Data Science Certifications

Data Science 101

Read to the end to learn more about a new study group I will be launching. In Late January 2019, Microsoft launched 3 new certifications aimed at Data Scientists/Engineers. For a while, Microsoft has been toying with different methods for training and credentials. They launched the Microsoft Professional Program in Data Science back in 2017. While it provides great content, it did not result in either a college diploma or an official Microsoft certification.

More Trending

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How a California county is using data and AI to help citizens in need

IBM Big Data Hub

Leveraging IBM cloud and partnered with IBM leaders, Sonoma County transformed with data and Watson AI.

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Hands-On Introduction to creditR: An Amazing R Package to Enhance Credit Risk Scoring and Validation

Analytics Vidhya

Introduction Machine learning is disrupting multiple and diverse industries right now. One of the biggest industries to be impacted – finance. Functions like fraud. The post Hands-On Introduction to creditR: An Amazing R Package to Enhance Credit Risk Scoring and Validation appeared first on Analytics Vidhya.

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It’s True: Educate a Woman, Educate a Nation

Sisense

Despite progress in recent years, UNESCO says that more girls than boys remain out of school. In fact, according to the UNESCO Institute for Statistics , “16 million girls will never set foot in a classroom – and women account for two-thirds of the 750 million adults without basic literacy skills.”. There’s a widely-known African proverb that says “If you educate a man, you educate an individual.

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NLP Learning Series: Part 3 - Attention, CNN and what not for Text Classification

MLWhiz

This post is the third post of the NLP Text classification series. To give you a recap, I started up with an NLP text classification competition on Kaggle called Quora Question insincerity challenge. So I thought to share the knowledge via a series of blog posts on text classification. The first post talked about the different preprocessing techniques that work with Deep learning models and increasing embeddings coverage.

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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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How to control costs and simplify life with IBM Hybrid Data Management Platform

IBM Big Data Hub

The IBM Hybrid Data Management Platform provides simplicity and control in one package for your hybrid architecture needs or journey to the cloud.

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DataHack Radio #19: The Path to Artificial General Intelligence with Professor Melanie Mitchell

Analytics Vidhya

Introduction “People underestimate how complex intelligence is.” How close are we to Artificial General Intelligence (AGI)? It seems we take a step closer to. The post DataHack Radio #19: The Path to Artificial General Intelligence with Professor Melanie Mitchell appeared first on Analytics Vidhya.

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Automate Consolidations with the Magic of Jet Reports – Webinar April 11, 2019

Jet Global

One of the most common manual reporting interventions users of Microsoft Dynamics NAV, GP, and 365 Business Central makes is financial report consolidations – whether it’s across multiple companies, departments, or other dimensions. But with Jet Reports, you can do this automagically! Instead of wasting one more hour, or risking one more reporting error with copying, pasting, exporting, and labor-intensive composition for multi-company or multi-department reports, attend this month’s Success Ser

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Free Data Science University Course Notes

Data Science 101

University can be a great way to learn data science. However, many universities are very expensive, difficult to get admitted, or not geographically feasible. Luckily, a few of them are willing to share data science, machine learning and deep learning materials online for everyone. Here is just I small list I have come across lately. MIT Deep Learning – Lecture notes, slides and guest talks about deep learning and self driving cars Introduction to Artificial Intelligence from UC Berkeley &

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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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4 Reasons Why GRC Is a Useless Term

John Wheeler

It has been 5 years since Gartner embarked on the journey to enhance our coverage of the risk management technology marketplace. That journey included in-depth survey research and countless interactions with our end-user clients to understand their need to better manage strategic, operational and IT/cybersecurity risks. These end-user needs and resulting demand led to the definition of a new technology marketplace – integrated risk management (IRM).

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Keynote Takeaways From Gartner Data & Analytics Summit

Sisense

Every year there’s high anticipation to see what key message Gartner will present in the yearly Data & Analytics Summits. The BI industry takes Gartner’s perspective very seriously, and year after year, it’s very common to see messages that were first described in the Gartner summits making their way into the websites of many analytics vendors.

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Continuous availability of data drives continuous intelligence

IBM Big Data Hub

Bring our unified POV on Data Replication and its impact on driving analytics initiatives to counter Qlik buying Attunity. .

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Data Visualization Society Launches

Data Science 101

A new community for data visualization professionals has launched. It is called the Data Visualization Society. According to the website, The Data Visualization Society aims to collect and establish best practices and foster community to support its members as they develop their data visualization skills. Currently, membership is free and they are looking for help growing the community.

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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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AI vs. BI for Business, What Do You Need?

Jet Global

With all the attention being paid to artificial intelligence (AI) these days, it’s no surprise that enterprise leaders are scrambling to find ways to shoehorn AI implementations into their technology stack. But when you ask leaders in the enterprise to define what they’re looking for from AI, their answers frequently focus on solutions that will empower better business decision making.

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Role of Workforce Analytics in Event Industry

BizAcuity

Workforce Analytics – What is its need for companies. Workforce Analytics in simple terms can be defined as an advanced set of software and methodology tools that measures, characterizes, and organizes sophisticated employee data and these tools helps in understanding the employee performance in a logical way. Human resource leaders are using workforce analytics under various forms such as predictive and prescriptive analytics.

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Simplifying Db2 downloads to help clients and developers get started

IBM Big Data Hub

Instead of choosing between multiple download options, anyone can now download and use a single, full-featured version of Db2 for as long as they want, without paying fees, contacting an IBM sales person, providing a credit card, getting on a mailing list or enduring adware.

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Our Obsession with Continuous Testing

DataRobot

In a previous blog post , we introduced you to Zach Deane-Mayer, a data scientist who runs our core modeling team. One of the most important tools in his team’s arsenal is a data science performance evaluation system created and maintained by our QA team. This system is at the core of our comprehensive testing philosophy that we believe is crucial to delivering a platform that our customers can trust, no matter what DataRobot features they’re using or how they’ve chosen to deploy them.

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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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Better Preference Predictions: Tunable and Explainable Recommender Systems

Insight

Ad recommendations should be understandable to the individual consumer, but is it possible to increase interpretability without sacrificing accuracy? Internet of Thing (AWS IoT) Are you looking to transition into the field of machine learning in Silicon Valley, New York, or Toronto? Apply for the upcoming June session today ( Deadline is March 25th for SV and NYC ) or learn more about the Artificial Intelligence program at Insight!

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Help for Academic Programs in Data Science

Data Science 101

Brandon Rohrer (along with others ) created an excellent resource for academic programs, Industry recommendations for academic data science programs. The resource is authored by a number of industry data scientists and university faculty. It is collection of useful information for college data science programs. Here are some of the topics: What do Industry data scientists do?

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Building a Diverse and Inclusive Teradata

Teradata

Teradata CEO Oliver Ratzesberger celebrates International Women's Day.

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From Machine Learning to Business Learning

Decision Management Solutions

Machine learning is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on models and inference instead. It is seen as a subset of artificial intelligence. — Wikipedia. Machine Learning is increasingly widely used to make predictions.

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

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

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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Training a Champion: Building Deep Neural Nets for Big Data Analytics

Sisense

The world of data is now the world of Big Data. The genie is out of the bottle and there’s no going back. We produce more and more data every day and the datasets being generated are getting more and more complex. Traditionally, the way to handle this has been to scale up computing resources to handle these bigger datasets. That’s not feasible for the long term on a global scale, nor is it tenable in the near term for smaller organizations who may have limited resources to deal with their analyt

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Avoiding Human Error When Building Artificial Intelligence

DataRobot

Can You Trust That Your AI Was Built Correctly? It has been more than three years since the last time I competed in a data science competition, and yet there’s one memory about that competition that remains vivid in my mind. I had spent a busy week at my computer coding up a cool-looking solution, and I was ready to submit my first entry to the competition.

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Breaking Boundaries in Sales with AI

bridgei2i

If we are not actively engaged in industries related to technology, we may fail to fully appreciate how we might already be influenced by artificial intelligence in our day-to-day world. Everyone is talking about self-driving cars, seemingly inanimate objects conversing with you about your personal preferences, someone somewhere already seems to recommend your shopping list armed with the knowledge of what you like or dislike.

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Data Governance Stock Check: Using Data Governance to Take Stock of Your Data Assets

erwin

For regulatory compliance (e.g., GDPR) and to ensure peak business performance, organizations often bring consultants on board to help take stock of their data assets. This sort of data governance “stock check” is important but can be arduous without the right approach and technology. That’s where data governance comes in …. While most companies hold the lion’s share of operational data within relational databases, it also can live in many other places and various other formats.

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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.