- When Correlation is Better than Causation - Aug 18, 2021.
Identifying causality in an analysis isn't always practical. We show a heuristic approach for using correlations to inform decisions.
- The 8 Basic Statistics Concepts for Data Science - Jun 24, 2020.
Understanding the fundamentals of statistics is a core capability for becoming a Data Scientist. Review these essential ideas that will be pervasive in your work and raise your expertise in the field.
- The Hidden Risk of AI and Big Data - Sep 20, 2019.
With recent advances in AI being enabled through access to so much “Big Data” and cheap computing power, there is incredible momentum in the field. Can big data really deliver on all this hype, and what can go wrong?
- Why Ice Cream Is Linked to Shark Attacks – Correlation/Causation Smackdown - Jan 19, 2019.
Why are soda and ice cream each linked to violence? This article delivers the final word on what people mean by "correlation does not imply causation."
- Key Takeaways from KDD 2018: a Deconfounder, Machine Learning at Pinterest, Knowledge Graph - Sep 11, 2018.
Highlights and key takeaways from KDD 2018, 24th ACM SIGKDD conference on Data Science and Data Mining: including what is a deconfounder, how Pinterest approaches Machine Learning, Knowledge Graph for Products, and Differential Privacy.
- Top KDnuggets tweets, Jul 18-24: Causation in a Nutshell - Jul 25, 2018.
Also fast.ai Deep Learning Part 2 Complete Course Notes; Comparison of Top 6 Python #NLProc Libraries.
- Causation in a Nutshell - Jul 20, 2018.
Every move we make, every breath we take, and every heartbeat is an effect that is caused. Even apparent randomness may just be something we cannot explain.
- THE BOOK OF WHY: The New Science of Cause and Effect - May 15, 2018.
A Turing Prize-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize AI.
- 12 Useful Things to Know About Machine Learning - Apr 12, 2018.
This is a summary of 12 key lessons that machine learning researchers and practitioners have learned include pitfalls to avoid, important issues to focus on and answers to common questions.
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- Causation: The Why Beneath The What - Aug 18, 2017.
A lot of marketing research is aimed at uncovering why consumers do what they do and not just predicting what they'll do next. Marketing scientist Kevin Gray asks Harvard Professor Tyler VanderWeele about causal analysis, arguably the next frontier in analytics.
- Top KDnuggets tweets, Jul 26 – Aug 01: 37 Reasons why your #NeuralNetwork is not working; Machine Learning Exercises in Python - Aug 2, 2017.
Also Hill criteria for #causality vs #correlation via #xkcd cartoons; #MachineLearning Workflows in #Python from Scratch Part 2: k-means Clustering
- Causation or Correlation: Explaining Hill Criteria using xkcd - Feb 20, 2017.
This is an attempt to explain Hill’s criteria using xkcd comics, both because it seemed fun, and also to motivate causal inference instructures to have some variety in which xkcd comic they include in lectures.
- Top KDnuggets tweets, Feb 11-12: Automating romance with Eigenfaces; My Brief Guide to Big Data, Predictive Analytics for non-experts - Feb 13, 2015.
Romantic #DataScientist @crockpotveggies automates #Tinder with Eigenfaces; My Brief Guide to Big Data and Predictive Analytics for non-experts; #DataMining finds corruption is correlated with low income, low development MIT; Hitachi buys Pentaho to extend Its #BigData footprint.
- Can noise help separate causation from correlation? - Jan 21, 2015.
How to tell correlation from causation is one of the key problems in data science and Big Data. New Additive Noise Models methods can do it with over 65% accuracy, opening new breakthrough possibilities.
- Top stories for Jan 4-10: 11 Clever Methods of Overfitting; Research Leaders on Data Science and Big Data - Jan 11, 2015.
11 Clever Methods of Overfitting and how to avoid them; Causation vs Correlation: Visualization, Statistics, and Intuition; Research Leaders on Data Science and Big Data key trends, top papers; Differential Privacy: How to make Privacy and Data Mining Compatible.
- Top KDnuggets tweets, Dec 29 – Jan 04: A brilliant way to tell causation from correlation; Machine Learning Experts You Need to Know. - Jan 5, 2015.
SAS is n1 among major BI vendors whose users plan to discontinue use; How #MachineLearning, #BigData, and image recognition could revolutionize search; A brilliant way to tell causation from correlation; Machine Learning Experts You Need to Know: Geoff Hinton, Michael Jordan, Andrew Ng.
- Causation vs Correlation: Visualization, Statistics, and Intuition - Jan 4, 2015.
Visualizations of correlation vs. causation and some common pitfalls and insights involving the statistics are explored in this case study involving stock price time series.
- Top KDnuggets tweets, Dec 22-28: Top 10 Data Science Skills, and How to Learn Them; How to tell correlation from causation - Dec 29, 2014.
Top 10 Data Science Skills, and How to Learn Them; Mathematicians claim to figure out how to tell correlation from causation; Review of #MOOC Learning from Data - the class that changed everything; Free Big Data sources every Data Science enthusiast should know.
- Interview: Amy Gaskins, AVP, MetLife on Smarter Analytics through Qualitative Research - Jul 22, 2014.
We discuss the relevance of qualitative research for customer intelligence, MetLife Infinity, and the increasing trend of behavior-based customer segmentation.
- Top stories for Jun 8-14 - Jun 15, 2014.
KDnuggets 15th Annual Analytics, Data Mining, Data Science Software Poll: RapidMiner Continues To Lead; Data Lakes vs Data Warehouses; The First Law of Data Science: Do Umbrellas Cause Rain? Huge Big Data Poster and Reference.
- Top KDnuggets tweets, Jun 9-10: Numeric Matrix Manipulation: Cheat Sheet; The First Law of Data Science - Jun 11, 2014.
Also - The First Law of Data Science: Do Umbrellas Cause Rain? ; Tell Your Kids to be Data Scientists - Not Doctors; DLib Library for Machine Learning
- The First Law of Data Science: Do Umbrellas Cause Rain? - Jun 9, 2014.
Michael Brodie on the first law of data science, the role of data curation in Big Data analysis, and Thomas Piketty economic theories.