- KDnuggets: Personal History and Nuggets of Experience - Nov 30, 2021.
After 28+ years of publishing and editing KDnuggets, I am retiring and transitioning KDnuggets to Matthew Mayo, who will become the new editor-in-chief. I want to share with you my story of KDnuggets and highlight some of the useful nuggets of experience I learned along this amazing journey.
About Gregory Piatetsky, About KDnuggets, History
- High Performance Deep Learning, Part 1 - Jun 18, 2021.
Advancing deep learning techniques continue to demonstrate incredible potential to deliver exciting new AI-enhanced software and systems. But, training the most powerful models is expensive--financially, computationally, and environmentally. Increasing the efficiency of such models will have profound impacts in many ways, so developing future models with this intension in mind will only help to further expand the reach, applicability, and value of what deep learning has to offer.
Deep Learning, Efficiency, History, Machine Learning
- 2011: DanNet triggers deep CNN revolution - Feb 4, 2021.
In 2021, we are celebrating the 10-year anniversary of DanNet, which, in 2011, was the first pure deep convolutional neural network (CNN) to win computer vision contests. Read about its history here.
AI, Convolutional Neural Networks, History, Jurgen Schmidhuber, Neural Networks
- Data Science History and Overview - Nov 30, 2020.
In this era of big data that is only getting bigger, a huge amount of information from different fields is gathered and stored. Its analysis and extraction of value have become one of the most attractive tasks for companies and society in general, which is harnessed by the new professional role of the Data Scientist.
About Gregory Piatetsky, Data Science, Data Scientist, History, Python
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.
Attention, Deep Learning, GANs, History, ImageNet, Reinforcement Learning, Transformer
- 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.
Foster Provost, History, Machine Learning, Tom Fawcett
- 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.
Anonymity, Anonymized, History, Netflix, Privacy
- 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.
Baseball, History, Sports, TIBCO, Time Series
- 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.
Explained, History, Machine Learning, Neural Networks, Perceptron
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.
Career, Data Science, Data Scientist, History, Machine Learning, Tips, Trends
- 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.
AGI, AI, Deep Learning, History, Hype, Jobs, Machine Learning
- 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.
AI, Big Data, History, Machine Learning, Neural Networks, Reinforcement Learning, Trends
- 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.
AI, Alan Turing, Herbert A. Simon, History, Hype, Marvin Minsky, Neural Networks
- 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.
Big Data, Big Data Analytics, Data Analysis, Data Science, History
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.
Pages: 1 2
Andrew Ng, Big Data, Deep Learning, Geoff Hinton, Google, GPU, History, Neural Networks, NVIDIA
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.
AI, Artificial Intelligence, History, ImageNet
- 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.
Big Data, Doug Laney, History, Tim O'Reilly
- 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.
History, Isabelle Guyon, Support Vector Machines, SVM, Vladimir Vapnik
- 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.
About Gregory Piatetsky, Alan Turing, Bayes Theorem, Data Mining, DJ Patil, History, Vladimir Vapnik
- 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.
Automation, Data Science, Future, History, Robots
- 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.
About Gregory Piatetsky, Data Science, History
