2017 Jul Opinions, Interviews
All (100) | Courses, Education (4) | Meetings (15) | News, Features (16) | Opinions, Interviews (26) | Software (2) | Tutorials, Overviews (30) | Webcasts & Webinars (7)
- Digital Transformation through Data Democratization - Jul 31, 2017.
Digital innovators will succeed because enterprise data doesn’t belong to silos and data has immense value, but only if available as a “whole”, to allow full picture of the enterprise rather than short term trends or baseline BI reports.
- The Key to Data Monetization - Jul 31, 2017.
While I have talked frequently about the concept of Analytic Profiles, I’ve never written a blog that details how Analytic Profiles work. So let’s create a “Day in the Life” of an Analytic Profile to explain how an Analytic Profile works to capture and “monetize” your analytic assets.
- When Data Science Is Not Enough: Deriving Signal from Maritime Observations - Jul 28, 2017.
We examine the limits of "data science-first" thinking - letting technical skills drive the analysis, and only later adding domain understanding.
- Machine Learning and Misinformation - Jul 27, 2017.
The creative aspects of machine learning are overshadowed by visions of an autonomous future, but machine learning is a powerful tool for communication. Most machine learning in today’s products is related to understanding.
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The BI & Data Analysis Conundrum: 8 Reasons Why Many Big Data Analytics Solutions Fail to Deliver Value - Jul 26, 2017.
Why many BI & Analytics projects/solutions fail to deliver the business value? Let’s find out the answers to such questions. -
6 Reasons Why Python Is Suddenly Super Popular - Jul 25, 2017.
Python is a general-purpose language — sometimes referred to as utilitarian — which is designed to be simple to read and write. The point that it’s not a complex language is important.
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When not to use deep learning - Jul 24, 2017.
Despite DL many successes, there are at least 4 situations where it is more of a hindrance, including low-budget problems, or when explaining models and features to general public is required.
- Top Quora Data Science Writers and Their Best Advice, Updated - Jul 24, 2017.
Get some insight into tips and tricks, the future of the field, career advice, code snippets, and more from the top data science writers on Quora.
- Optimism about AI improving society is high, but drops with experience developing AI systems - Jul 21, 2017.
While about 60% of KDnuggets readers think AI and Automation will improve society, the optimism drops significantly among those with 4 or more years experience developing AI systems. Should we pay more attention to the experts?
- AI and Deep Learning, Explained Simply - Jul 21, 2017.
AI can now see, hear, and even bluff better than most people. We look into what is new and real about AI and Deep Learning, and what is hype or misinformation.
- Intelligence and Cognition: I Do Not Think They Mean What You Think They Mean - Jul 21, 2017.
You have likely noticed the recent relative uptick in the use of the words "intelligence" and "cognitive," as well as their derivatives. Are such terms really true or are they a marketing device?
- Emotional Intelligence for Data Science Teams - Jul 20, 2017.
Here are three lessons for making and demonstrating a greater business impact to your organization, according to Domino Labs most successful customers.
- Top Modules and Features of Business Intelligence Tools - Jul 18, 2017.
What makes BI tools great? What features are important while selecting a good BI tool? Let’s have a look.
- Artificial Intuition – A Breakthrough Cognitive Paradigm - Jul 18, 2017.
This article is just a reflection of my current understanding of the language of Deep Learning Meta Meta-Model. That’s definitely a mouth full, so to make life simpler for everyone, I just call this the Deep Learning Canonical Patterns.
- Are Most Machine Learning Experts Turning to Deep Learning? - Jul 18, 2017.
Read a short opinion on what the impact of machine learning researchers focusing on deep learning will be.
- How GDPR Affects Data Science - Jul 17, 2017.
Coming European GDPR directive affects data science practice mainly in 3 areas: limits on data processing and consumer profiling, a “right to an explanation” for automated decision-making, and accountability for bias and discrimination in automated decisions.
- How to Turn your Data Science Projects into a Success - Jul 14, 2017.
This interview with Dr. Olav Laudy, Chief Data Scientist for IBM Analytics, is a summary of a recent conference where he participated in a panel on the Big Data and Analytics
- Marketing Analytics for Data Rich Environments - Jul 14, 2017.
A lot is changing in the world of marketing analytics. Marketing scientist Kevin Gray asks Professor Michel Wedel, a leading authority on this topic from the Robert H. Smith School of Business at the University of Maryland, what marketing researchers and data scientists most need to know about it.
- The 4 Types of Data Analytics - Jul 13, 2017.
We focus on the four types of data analytics we encounter in data science: Descriptive, Diagnostic, Predictive and Prescriptive.
- Why Every Company Needs a Digital Brain - Jul 11, 2017.
As emerging technologies like AI/machine learning are adopted across different parts of the business, enterprises require a “digital brain” to coordinate those efforts and generate systemic intelligence.
- The Strange Loop in Deep Learning - Jul 11, 2017.
This ‘strange loop’ is in fact is the fundamental reason for what Yann LeCun describes as “the coolest idea in machine learning in the last twenty years.”
- Data Science Governance - Why does it matter? Why now? - Jul 10, 2017.
Everyone is talking about GDPR, Data Governance and Data Privacy, these days. Here we discuss what is it and why does it matter.
- Improving Zillow Zestimate with 36 Lines of Code - Jul 7, 2017.
We built this project as a quick and easy way to leverage some of the amazing technologies that are being built by the data science community!
- Apache Flink: The Next Distributed Data Processing Revolution? - Jul 5, 2017.
Will Apache Flink displace Apache Spark as the new champion of Big Data Processing? We compare Spark and Apache Flink performance for batch processing and stream processing.
- What Advice Would You Give Your Younger Data Scientist Self? - Jul 5, 2017.
I was asked this question recently via LinkedIn message: "What advice would you give your younger data scientist self?" The best piece of advice I honestly think I can give is this: Forget about "data science."
- Text Clustering : Quick insights from Unstructured Data, part 2 - Jul 4, 2017.
We will build this in a modular way and also focus on exposing the functionalities as an API so that it can serve as a plug and play model without any disruptions to the existing systems.
The BI & Data Analysis Conundrum: 8 Reasons Why Many Big Data Analytics Solutions Fail to Deliver Value
6 Reasons Why Python Is Suddenly Super Popular
When not to use deep learning
The 4 Types of Data Analytics
Jun
