- Skynet Is Real: The History and Future of Factories With No Workers - Mar 16, 2020.
Let’s see whether robots will become "grave diggers" of the proletariat, what do we lack to get total automation, and what compromises exist.
- Top 5 AI trends for 2020 - Jan 21, 2020.
We are all witnessing a staggering growth of AI technology with so many new benefits for people while also changing the way we live and work. As AI continues to grow, which applications will have a significant impact in 2020?
- Python, Selenium & Google for Geocoding Automation: Free and Paid - Nov 21, 2019.
This tutorial will take you through two options that have automated the geocoding process for the user using Python, Selenium and Google Geocoding API.
- 3 Reasons Why AutoML Won’t Replace Data Scientists Yet - Mar 6, 2019.
We dispel the myth that AutoML is replacing Data Scientists jobs by highlighting three factors in Data Science development that AutoML can’t solve.
- Free Access: Intelligent Automation Report - Feb 12, 2019.
Learn the top challenges in the world of Intelligent Automation, the main trends in RPA, AI, Machine Learning, and key areas of spend for technologies in 2019. Get the report!
- Top 10 Technology Trends of 2019 - Feb 7, 2019.
This article outlines 10 top trending technologies for 2019, a list which covers diverse topics such as security, IoT, reinforcement learning, energy sustainability, smart cities, and much more.
- Robotic Process Automation in the Nordics - Jan 29, 2019.
Read this white paper to discover what the future has in store for robotic automation, as well as the current limitations of RPA, how to move past these limitations, why an intelligent future is the natural progression for RPA, and more.
- How will automation tools change data science? - Dec 18, 2018.
This article provides an overview of recent trends in machine learning and data science automation tools and addresses how those tools will change data science.
- AI, Data Science, Analytics Main Developments in 2018 and Key Trends for 2019 - Dec 3, 2018.
Review of 2018 and Predictions for 2019 from our panel of experts, including Meta Brown, Tom Davenport, Carla Gentry, Bob E Hayes, Cassie Kozyrkov, Doug Laney, Bill Schmarzo, Kate Strachnyi, Ronald van Loon, Favio Vazquez, and Jen Underwood.
- Anticipating the next move in data science – my interview with Thomson Reuters - Nov 17, 2018.
Like chess, Big Data is a combination of science, art and play; Gregory Piatetsky-Shapiro of KDnuggets helps data devotees discover winning moves - my Thomson Reuters interview.
- Cartoon: Data Scientist was the sexiest job of the 21st century until … - Jul 14, 2018.
This Data Scientist thought that he had the sexiest job of the 21st century until the arrival of the competition ...
- AI Solutionism - Jul 12, 2018.
Machine learning has huge potential for the future of humanity — but it won’t solve all our problems.
- The 4 Levels of Data Usage in Data Science - Jul 9, 2018.
This is an overview of the 4 levels, or "buckets," of data usage in business, starting at monitoring and progressing to automation.
- The Future of Artificial Intelligence: Is Your Job Under Threat? - Jun 1, 2018.
This article examines the rapid growth of artificial intelligence: how we got to this point, the future AI job market and what can be done.
- Hear the latest AI advancements in robotics & automation from Uber, Hitachi, Google & more - Apr 26, 2018.
The Summits will bring together 550 experts and 60 speakers using AI and deep learning to improve operations in manufacturing, and creating the next generation of intelligent robots. Save 20% with code KDNUGGETS.
- ML Powering Marketing Automation: New Guidebook - Apr 24, 2018.
Understanding and quantifying a customer's journey - otherwise known as marketing attribution - is essential for marketers to analyze the ROI from campaigns. Get the latest guidebook to understand how its done!
- When Do We Trust Machines? - Apr 16, 2018.
We propose a framework of "trust heatmap", show how the trust in machines depends on two key elements: their error rate and the costs of mistakes, and examine the automation frontier.
- Meet experts in AI & Industrial Automation in San Francisco: Save with KDnuggets - Mar 13, 2018.
This June 18-19, RE-WORK will be returning to San Francisco to host the Deep Learning for Robotics Summit and the AI in Industrial Automation Summit. Save 20% with the code KDNUGGETS
- Preventing Claims with Automation, IoT and Connected Services (Webinar, Feb 23) - Feb 15, 2018.
This webinar will give you the insights to stay ahead of the curve of innovation, including Real-Time Risk Assessment, Automatically Turning Data to Action, and more.
- Deep Feature Synthesis: How Automated Feature Engineering Works - Feb 7, 2018.
Automating feature engineering optimizes the process of building and deploying accurate machine learning models by handling necessary but tedious tasks so data scientists can focus more on other important steps.
- 2018 Predictions for the Analytics & Data Science Hiring Market - Feb 6, 2018.
What do you think of this year’s predictions? Do you see any new tools on the horizon, or do you believe data science popularity is due for a reckoning of sorts?
- 5 things that will be important in data science in 2018 - Jan 11, 2018.
What’s data science going to look like in 2018? How are job roles in the field going to change? Will AI find new ways to capture the public imagination? Learn more from Packt $5 books - on sale till Jan 16.
- Everything Changes: A Human Perspective on Digitization - Jan 2, 2018.
An insightful, thought-provoking article on digital disruption and evolution of technology.
- DataRobot: Moving from BI to Machine Learning with Automation - Dec 4, 2017.
Analytics industry expert Jen Underwood shares the fast path to developing world-class predictive modeling capabilities.
- Fusing Human and Machine for Seamless, Automated Insurance Claims (Webinar, Dec 14) - Nov 28, 2017.
Insurance claims is standing on the brink of transformation with new technology uncovering opportunities to process claims more efficiently and provide a superior customer experience. Learn about the oportunities in this Dec 14 Webinar.
- The ways that AI can change your business - Oct 20, 2017.
AI technology involves a change in the value chain and represents a major challenge and opportunity for businesses. Managers are directly involved in this challenge, by accompanying the teams through this transition: vanquish fears, embracing innovation, transforming businesses, training teams.
- Big Data or Big BS? - Sep 7, 2017.
Data and analysis of data have, in some form, been used to aid decision making since ancient times. So why, after all these centuries are data and analytics not more embedded in corporate decision making?
- Are physicians worried about computers machine learning their jobs? - Aug 30, 2017.
We review JAMA article on “Unintended Consequences of Machine Learning in Medicine” and argue that a number of alarming opinions in this pieces are not supported by evidence.
- 4 Industries Being Transformed by Machine Learning and Robotics - Aug 15, 2017.
When used in combination with big data and machine learning, both AI and robotics can actively improve over time as they collect more information. You don’t have to look far to see how these technologies have revolutionized the world, and continue to do so.
- 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?
- Turn Data to Gold: Deploy Real-Time Analytics to Maximize Insurance IoT (Webinar, July 25) - Jul 12, 2017.
Join experts from leading firms for discussion how to take advantage of future insurance opportunities using the key to unlocking IoT data – real-time analytics.
- New Poll: Will society become better from increased automation, AI, and Machine Learning? - Jul 9, 2017.
What will be the impact on human society and human welfare of increased automation, AI, and Machine Learning? Please vote.
- Role of the Data Scientist in the B2B Era - Jun 20, 2017.
In businesses everywhere, the digital transformation is spawning a bunch of new job titles. Among them are Chief Data Officer, Big Data Architect and Data Visualizer. All these sought-after specialist data roles are having a major impact on the workplace.
- The Real “Fear” of AI is Automation Inundation - Jun 16, 2017.
The biggest threat to minimum wage earners (and beyond, quite frankly) is the new tsunami of automation in the workplace.
- Will Data Science Eliminate Data Science? - May 25, 2017.
There are elements of what we do which are AI complete. Eventually, Artificial General Intelligence will eliminate the data scientist, but it’s not around the corner.
- Exclusive: Interview with Jeremy Howard on Deep Learning, Kaggle, Data Science, and more - Jan 14, 2017.
My exclusive interview with rock star Data Scientist Jeremy Howard, on his latest Deep Learning course, what is needed for success in Kaggle, how Enlitic is transforming medical diagnostics, and what Data Scientists should do to create value for their organization.
- Ethical Implications Of Industrialized Analytics - Nov 29, 2016.
Analytics & Big Data will be involved in every aspect of our lives and we should handle the ethical dilemmas wisely to let innovation contribute more to our lives.
- Transform the Future with Predictive Analytics - Nov 10, 2016.
Visit SAP resource center to learn how to accelerate decisions with automated predictive techniques and results, deploy and manage thousands of predictive data sets and test-drive a fully functional copy of SAP BusinessObjects Predictive Analytics software.
- Automating Data Ingestion: 3 Important Parts - Sep 9, 2016.
In the day and age of ‘Big Data”, data ingestion has to be automated on some level. How best to automate it?
- Cartoon: When Automation Goes Too Far - Apr 30, 2016.
KDnuggets Cartoon looks into the future of Automated Data Science and Marketing - when will automation go too far?
- Top KDnuggets tweets, Jun 16-22: Deep Learning resources from O’Reilly; Free Kaggle Machine Learning Tutorial in R - Jun 23, 2015.
#DeepLearning resources from @OReillyMedia to help you get started; Free @Kaggle #MachineLearning Tutorial in R - learn how to compete in #DataScience; Data Scientists, enjoy your fat salaries while you can; Computational Aesthetics #Algorithm Spots #Beauty That Humans Overlook.
- I’ve Been Replaced by an Analytics Robot - May 20, 2015.
A veteran statistician reflects on the journey from a statistician of the past to data scientist of today, how the work he used to do became automated, and what future can data scientists can expect.
- Data Scientists Automated and Unemployed by 2025? - May 5, 2015.
Will Data Scientists be unemployed by 2025? Majority of voters in latest KDnuggets Poll expect expert-level Data Science to be automated in 10 years or less.
- KDnuggets Poll: Future of Predictive Analytics: Human or Machine? - Apr 21, 2015.
The robots are taking over many jobs - will they take yours and mine? New KDnuggets Poll is asking if and when automation will reach the level of human data scientists.
- The Imminent Future of Predictive Modeling - Apr 21, 2015.
Predictive modeling tools and services are undergoing an inevitable step-change which will free data scientists to focus on applications and insight, and result in more powerful and robust models than ever before. Amongst the key enabling technologies are new hugely scalable cross-validation frameworks, and meta-learning.
- KDnuggets™ News 15:n06, Feb 25: My brief guide to Big Data; Data Scientist 3 wishes; Active Data Mining Blogs - Feb 25, 2015.
My Brief Guide to Big Data; Cartoon: Data Scientist gets 3 wishes for Valentine Day; Active Data Mining, Data Science blogs; Gartner 2015 Magic Quadrant for Advanced Analytics - gainers and losers.
- Top stories for Feb 15-21: 10 things statistics taught us about big data analysis; History of Data Science in 5 strands - Feb 22, 2015.
My Brief Guide to Big Data and Predictive Analytics for non-experts; 10 things statistics taught us about big data analysis; History of Data Science Infographic in 5 strands; Automatic Statistician and the Profoundly Desired Automation for Data Science.
- Automatic Statistician and the Profoundly Desired Automation for Data Science - Feb 17, 2015.
The Automatic Statistician project by Univ. of Cambridge and MIT is pushing ahead the frontiers of automation for the selection and evaluation of machine learning models. In general, what does automation mean to Data Science?