Fri.Oct 18, 2019

3 Concepts Defining the Future of Work: Data, Decentralisation and Automation


The organisation of tomorrow will look fundamentally different than today's organisation. Those enterprises that are aware of the upcoming changes can best prepare and achieve competitive advantage in a data-driven society.

Approaching an Artificial Intelligence (AI) Strategy while Accounting for Bias


Approaching an Artificial Intelligence (AI) Strategy while Accounting for Bias. Datacon Africa DataCon Africa Insights

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The Tactile Internet?—?a New IoT?


The progress is constantly speeding up and the future is at our door?—?it it is something that everyone keeps repeating even not thinking much of this future. But if you start thinking, you find evidence to this in every tool, in every method and technique present in all spheres of life.

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Writing Your First Neural Net in Less Than 30 Lines of Code with Keras


Read this quick overview of neural networks and learn how to implement your first in very few lines using Keras. 2019 Oct Tutorials, Overviews Keras Neural Networks Python


ABCs of Data Normalization for B2B Marketers

Data normalization. It’s not a far stretch to suggest that the topic isn’t exactly what gets marketers excited in their day-to-day workflow. However, if lead generation, reporting, and measuring ROI is important to your marketing team, then data normalization matters - a lot. In this eBook, we’ll break down the ins and outs of data normalization and review why it’s so critical for your marketing strategies and goals!

How Cloud and Artificial Intelligence Help Modernize ERP


Digital transformation is around every corner in this world. Every company and user is following it to stay ahead among the competitors, get new opportunities, get introduced to the new markets and visualize how they do business.

5 Tips for Novice Freelance Data Scientists


If you want to launch your data science skills into freelance work, then check out these important tips to help you kick start your next adventure in data. 2019 Oct Opinions Advice Beginners Consulting Data Scientist

More Trending

2019 Gartner Magic Quadrant for Metadata Management Solutions


erwin positioned as a Leader in Gartner’s “2019 Magic Quadrant for Metadata Management Solutions”. We were excited to announce earlier today that erwin was named as a Leader in the @Gartner _inc “2019 Magic Quadrant for Metadata Management Solutions.”.

Featured New Research: 7 Must-Have Foundations for Modern Data and Analytics Governance

Andrew White

7 Must-Have Foundations for Modern Data and Analytics Governance. Data and analytics leaders can exploit business opportunities and challenges only if they have established the right foundations for data and analytics governance.

How to Get the Most out of ODSC West 2019


ODSC West comes to San Francisco on Oct 29 - Nov 1. With over 300 hours of content, 200+ speakers, and thousands of attendees, there is certainly a lot to see, learn, and do at the conference. Register by Friday for 10% off your pass. 2019 Oct Meetings CA Data Science ODSC San Francisco

Azure AZ101 Checklist of Materials

Jen Stirrup

Here is my checklist of Azure infrastructure handy materials that I use for AZ101 students as homework or additional class learning. I was asked for this by one of my students and I thought I’d share it here. The focus here is on just some of the topics and it is not exhaustive: Azure Migrate. Azure Site Recovery. Disaster Recovery. Azure Migrate. Currently, you can only create an Azure Migrate project in West Central US or East US region.

How to Solve 4 Common Challenges of Legacy Information Management

Speaker: Chris McLaughlin, Chief Marketing Officer and Chief Product Officer, Nuxeo

After 20 years of Enterprise Content Management (ECM), businesses still face many of the same challenges with finding and managing information. Join Chris McLaughlin, CMO and CPO of Nuxeo, as he examines four common business challenges that these legacy ECM systems pose and how they can be addressed with a more modern approach.

There is No Such Thing as a Free Lunch: Part 2 – Building an intelligent Digital Assistant


In this second part we want to outline our own experience building an AI application and reflect on why we chose not to utilise deep learning as the core technology used. 2019 Oct Tutorials, Overviews AI Deep Learning Machine Learning Optimization

Why data and analytics experts choose SPSS Statistics

IBM Big Data Hub

One could argue that many of the world’s problems can be solved with data. While I won’t be able to save the world just yet, I’d like to explain how statistical analysts and data experts use tools to understand data and how this data can then be managed to influence our environment

Blockchain in Healthcare: Greater Security, Fewer Mistakes, Less Paper

Sirius Computer Solutions

If the first thing that comes to mind when you hear “blockchain” is Bitcoin, you’re not alone. Cryptocurrencies were built on blockchain’s system of using distributed, permissioned computing to create a virtual ledger that could be used to confirm and ensure the accuracy and security of transactions.

Juice Squeezed: Is the Postseason Baseball Really Dead?


There have been anecdotal complaints that the postseason baseball is deader than its regular-season counterpart, so we used DataRobot to analyze 100k+ batted balls in 2019. AI Across Industries

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The 2019 Technographic Data Report for B2B Sales Organizations

In this report, ZoomInfo substantiates the assertion that technographic data is a vital resource for sales teams. In fact, the majority of respondents agree—with 72.3% reporting that technographic data is either somewhat important or very important to their organization. The reason for this is simple—sales teams value technographic data because it makes essential selling activities easier and more efficient.

How-To: Execute Anomaly Detection at Scale in 5 Easy Steps


Anomaly detection is an approach that can be useful across an array of industries and for a variety of purposes. But the underlying, unifying factor is the ability to detect small changes or differences in a system that might otherwise go unnoticed.