- Main 2021 Developments and Key 2022 Trends in AI, Data Science, Machine Learning Technology - Dec 10, 2021.
Our panel of leading experts reviews 2021 main developments and examines the key trends in AI, Data Science, Machine Learning, and Deep Learning Technology.
2022 Predictions, AI, Carla Gentry, Data Science, Doug Laney, Kate Strachnyi, Kirk D. Borne, Machine Learning, Predictions, Tom Davenport, Trends
Main 2020 Developments and Key 2021 Trends in AI, Data Science, Machine Learning Technology - Dec 9, 2020.
Our panel of leading experts reviews 2020 main developments and examines the key trends in AI, Data Science, Machine Learning, and Deep Learning Technology.
2021 Predictions, AI, AutoML, Bill Schmarzo, Carla Gentry, COVID-19, Doug Laney, GPT-3, Kirk D. Borne, Machine Learning, MLOps, Predictions, Ronald van Loon, Tom Davenport, Trends
13 must-read papers from AI experts - May 20, 2020.
What research articles do top AI experts in the field recommend? Find out which ones and why, then be sure to add each to your reading to do list.
AI, Andrew Ng, Hyperparameter, Kirk D. Borne, LSTM, Research
- Data Scientist’s Dilemma: The Cold Start Problem – Ten Machine Learning Examples - Jan 17, 2019.
We present an array of examples showcasing the cold-start problems in data science where the algorithms and techniques of machine learning produce the good judgment in model progression toward the optimal solution.
Cold Start, Data Scientist, Kirk D. Borne, Machine Learning
Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018 - Dec 12, 2017.
The leading experts in the field on the main Data Science, Machine Learning, Predictive Analytics developments in 2017 and key trends in 2018.
2018 Predictions, Carla Gentry, Data Science, Eric Siegel, Jeff Ullman, Jen Underwood, Jill Dyche, Kirk D. Borne, Machine Learning, Predictions, Rexer Analytics, Tom Davenport, Trends
Top 10 Active Big Data, Data Science, Machine Learning Influencers on LinkedIn, Updated - Sep 26, 2017.
Looking for advice? Guidance? Stories? We’ve put a list of the top ten LinkedIn influencers of the last three months, follow them and stay up-to-date with the latest news in Big Data, Data Science, Analytics, Machine Learning and AI.
About Gregory Piatetsky, Bernard Marr, Big Data, Carla Gentry, Data Science, DJ Patil, Influencers, Kirk D. Borne, LinkedIn, Machine Learning, Tom Davenport, Trends
- 42 Essential Quotes by Data Science Thought Leaders - May 4, 2017.
42 illuminating quotes you need to read if you’re a data scientist or considering a career in the field – insights from industry experts tackling the tough questions that every data scientist faces.
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Career, Data Science, Data Science Skills, Data Scientist, DJ Patil, Hilary Mason, Kirk D. Borne
Data Science, Predictive Analytics Main Developments in 2016 and Key Trends for 2017 - Dec 13, 2016.
Key themes included the polling failures in 2016 US Elections, Deep Learning, IoT, greater focus on value and ROI, and increasing adoption of predictive analytics by the "masses" of industry.
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2017 Predictions, Data Science, John Elder, Kirk D. Borne, Predictive Analytics, Tom Davenport
- Agilience Top Artificial Intelligence, Machine Learning Authorities - Nov 7, 2016.
Agilience developed a new way to find authorities in social media across many fields of interest. In previous post we reviewed the top authorities in Data Mining and Data science; in this post we review top authorities in Artificial Intelligence and Machine Learning which includes Vineet Vashishta, Kirk D. Borne, KDnuggets, James Kobielus, Kaggle and more.
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About KDnuggets, Agilience, AI, Artificial Intelligence, Influencers, Kaggle, Kirk D. Borne, Machine Learning
- AI and Machine Learning: Top Influencers and Brands - Mar 8, 2016.
Onalytica gives us a new list of the top 100 Artifical Intelligence and Machine Learning influencers and brands, and provides some insight into the relationships between them.
About Gregory Piatetsky, AI, Influencers, Kirk D. Borne, Machine Learning, Onalytica, Top list
21 Must-Know Data Science Interview Questions and Answers - Feb 11, 2016.
KDnuggets Editors bring you the answers to 20 Questions to Detect Fake Data Scientists, including what is regularization, Data Scientists we admire, model validation, and more.
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Bootstrap sampling, Data Science, Interview Questions, Kirk D. Borne, Precision, Recall, Regularization, Yann LeCun
- 20 Questions to Detect Fake Data Scientists - Jan 1, 2016.
Hiring Data Scientists is no easy job, particularly when there are plenty of fake posers. Here is a handy list of questions to help separate the wheat from the chaff.
Data Scientist, Data Visualization, import.io, Kirk D. Borne, Machine Learning, Outliers
- The 123 Most Influential People in Data Science - Sep 15, 2015.
We used LittleBird algorithm to build a true Data Science influencer network by measuring how often influencers retweet other influencers. Top influencers include @hmason, @kdnuggets, @kaggle, @peteskomoroch, @mrogati, and @KirkDBorne.
About KDnuggets, Alex Salkever, Big Data Influencers, Data Science, Hilary Mason, Influencers, Kaggle, Kirk D. Borne, Silk.co
- Most Viewed Big Data Videos on YouTube - May 9, 2015.
The top Big Data YouTube videos by those like Hortonworks and Kirk D. Borne cover diverse topics including Hadoop, Big Data Trends, Deep Learning, and Big Data Leadership.
Big Data, Cloudera, Deep Learning, Google, Grant Marshall, Hadoop, IBM, Kirk D. Borne, TED, Youtube
- IBM Big Data & Analytics Heroes - Feb 26, 2015.
IBM's Big Data & Analytics Heroes include leaders in the field that propel the industry in order to promote thought leadership and progress in Big Data Analytics.
About Gregory Piatetsky, Analytics Leader, Big Data, Big Data Analytics, IBM, Jake Porway, Kirk D. Borne
- Top 30 people in Big Data and Analytics - Feb 9, 2015.
Innovation Enterprise has compiled a top 30 list for individuals in big data that have had a large impact on the development or popularity of the industry.
About Gregory Piatetsky, Andy Palmer, Big Data, Big Data Influencers, DJ Patil, Hilary Mason, IE Group, Kirk D. Borne, Paco Nathan, Tom Davenport, Wolfram
- The Cardinal Sin of Data Mining and Data Science: Overfitting - Jun 14, 2014.
Overfitting leads to public losing trust in research findings, many of which turn out to be false. We examine some famous examples, "the decline effect", Miss America age, and suggest approaches for avoiding overfitting.
Dean Abbott, John Ioannidis, Kirk D. Borne, Overfitting, S&P 500
- Interview: Kirk Borne, Data Scientist, GMU on Big Data in Astrophysics and Correlation vs. Causality - May 30, 2014.
We discuss how to build the best data models, significance of correlation and causality in Predictive Analytics, and impact of Big Data on Astrophysics.
Correlation, Interview, Kirk D. Borne, Predictive Analytics, Recommendations
