- Deep Learning’s Most Important Ideas - Sep 14, 2020.
In the field of deep learning, there continues to be a deluge of research and new papers published daily. Many well-adopted ideas that have stood the test of time provide the foundation for much of this new work. To better understand modern deep learning, these techniques cover the basic necessary knowledge, especially as a starting point if you are new to the field.
- Top KDnuggets tweets, Aug 5-11: Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild - Aug 12, 2020.
Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild; How to Evaluate the Performance of Your Machine Learning Model; Deep Learning Most Important Ideas - an excellent review
- Tom Fawcett, in memoriam - Jun 17, 2020.
Foster Provost in memoriam for Tom Fawcett, killed on June 4th in a freak bicycle accident. Tom was a brilliant scholar, a selfless collaborator, a substantial contributor to Data Science for three decades, and a unique individual.
- Has AI Come Full Circle? A data science journey, or why I accepted a data science job - Apr 10, 2020.
Personal journeys in Data Science can vary greatly between individuals. Some are just getting starting and wading into this vast ocean of opportunity, and others have been involved during its decades-long evolution as a professional field. This review of a longer journey can provide a broader perspective of how you might fit into this interesting career.
- I Don’t Believe in Electrons - Apr 1, 2020.
What does it mean to believe in science? Does this notion of belief even make sense, or are scientists just supposed to be skeptics that question everything for all time, until we somehow arrive at some notion of Truth? And, what is science, anyway?
- Data Anonymization – History and Key Ideas - Oct 17, 2019.
While effective anonymization technology remains elusive, understanding the history of this challenge can guide data science practitioners to address these important concerns through ethical and responsible use of sensitive information.
- Using Time Series Encodings to Discover Baseball History’s Most Interesting Seasons - Sep 27, 2019.
Take me out to the ballgame! Take me out to the crowd! For the 2,829 seasons that have been played for 101 baseball teams since 1880, which seasons were unlike any others? Using SAX Encoding to recognize patterns in time series data, the most special years in baseball can be found.
- Neural Networks – an Intuition - Feb 7, 2019.
Neural networks are one of the most powerful algorithms used in the field of machine learning and artificial intelligence. We attempt to outline its similarities with the human brain and how intuition plays a big part in this.
- Should you become a data scientist? - Dec 10, 2018.
An overview of the current situation for data scientists, from its origins and history, to the recent growth in job postings, and looking at what changes the future might bring.
- Happy 25th Birthday, KDnuggets - Jul 23, 2018.
Twenty five years covering Data Mining, Knowledge Discovery in Data, KDD, Predictive Analytics, Big Data, Data Science, Machine Learning, and AI - my reflections on 25 years of publishing and editing KDnuggets.
- SuperDataScience Podcast: Insights from the Founder of KDnuggets - Jul 21, 2018.
I talk to Kirill Eremenko about my journey to data science, how KDnuggets started, why you should start honing your machine learning engineering skills at this very moment, what's the future of data science, and more.
- The Current Hype Cycle in Artificial Intelligence - Feb 28, 2018.
Over the past decade, the field of artificial intelligence (AI) has seen striking developments. As surveyed in, there now exist over twenty domains in which AI programs are performing at least as well as (if not better than) humans.
- Resurgence of AI During 1983-2010 - Feb 16, 2018.
We discuss supervised learning, unsupervised learning and reinforcement learning, neural networks, and 6 reasons that helped AI Research and Development to move ahead.
- The Birth of AI and The First AI Hype Cycle - Feb 13, 2018.
A dazzling review of AI History, from Alan Turing and Turing Test, to Simon and Newell and Logic Theorist, to Marvin Minsky and Perceptron, birth of Rule-based systems and Machine Learning, Eliza - first chatbot, Robotics, and the bust which led to first AI Winter.
- Did you know cavemen were already dealing with “Big Data” issues? - May 3, 2017.
We know Big Data & Analytics are new & cutting edge technologies; but actually, human started using data & analytics techniques 5000 years ago. Let’s take a look.
- Deep Learning – Past, Present, and Future - May 2, 2017.
There is a lot of buzz around deep learning technology. First developed in the 1940s, deep learning was meant to simulate neural networks found in brains, but in the last decade 3 key developments have unleashed its potential.
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- A Brief History of Artificial Intelligence - Apr 7, 2017.
This post is a brief outline of what happened in artificial intelligence in the last 60 years. A great place to start or brush up on your history.
- The Origins of Big Data - Feb 21, 2017.
Big Data has truly come of age in 2013 when OED introduced the term “Big Data” for the first time. But when was the term Big Data first used and Why? Here are the results of our investigation.
- Data Science & Ancestry - Dec 17, 2016.
Ancestry is curious topic for many people to find out their origin and history. Today, data science is used to help these people to dig into their family history and build the family trees.
- Data Mining History: The Invention of Support Vector Machines - Jul 4, 2016.
The story starts in Paris in 1989, when I benchmarked neural networks against kernel methods, but the real invention of SVMs happened when Bernhard decided to implement Vladimir Vapnik algorithm.
- KDnuggets™ News 16:n23, Jun 29: Machine Learning Trends & Future of AI; Data Science Kaggle Walkthrough; Regularization in Logistic Regression - Jun 29, 2016.
- History of Data Mining - Jun 22, 2016.
Data mining is a subfield of computer science which blends many techniques from statistics, data science, database theory and machine learning. Here are the major milestones and “firsts” in the history of data mining plus how it’s evolved and blended with data science and big data.
- 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.
- 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 KDnuggets tweets, Feb 16-22: History of Data Science across 5 strands; Most Popular Coding Languages of 2015 - Feb 23, 2015.
History of #DataScience across 5 strands; Most Popular Coding Languages of 2015: #Python 31% ...; #BigData reveals how information travels: 8 clusters in Europe; New Face Detection Algorithm to revolutionize search: finding faces no longer unique to humans.
- 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.
- Top KDnuggets tweets, Feb 16-17: Most Popular Coding Languages of 2015; History of Data Science across 5 strands - Feb 18, 2015.
Most Popular Coding Languages of 2015: #Python 31%, Java 20%, C++ 9.8%; History of #DataScience across 5 strands: CS, #Data, #Visualization, Math, Stats; IBM Verse new messaging software will use #Watson to declutter your inbox; Doctors store 1,600 digital #hearts for #BigData study.
- History of Data Science Infographic in 5 strands - Feb 17, 2015.
History of Data Science infographic presents key events in Data Science across 5 strands: Computer Science, Data Technology, Visualization, Mathematics/OR, and Statistics.