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Capri Granville's Discussions
Questions about A/B and Multivariate Testing
Started this discussion. Last reply by Sandy Ayer Jun 15. 1 Reply 1 Like
I want to test the optimum price for some items sold online. One way to do it is to set two different prices and do some A/B testing to see which price generates the most revenue, or comparing…Continue
Who is using regression models with interactions?
Started this discussion. Last reply by Andrew Reid Mar 15. 2 Replies 0 Likes
I believe biostatisticians use it, especially with small data sets, in the context of clinical trials, especially when using dummy variables (e.g. 0/1 for gender.) I am wondering how decision trees…Continue
AI: Miniaturization of Robots
Started this discussion. Last reply by Michael Rawson May 18, 2018. 2 Replies 1 Like
Maybe this seems like science fiction, but I was wondering if some companies are developing robots that are so small, that they are about the size of a virus. You could imagine a swarm of robotic…Continue
Is it better to overpredict, or underpredict?
Started this discussion. Last reply by Frank Raulf Jun 4. 6 Replies 3 Likes
Weather predictions are notoriously difficult for the Seattle area. I have seen many instances in which snow was predicted (say 1 to 3 inches) while the actual amount was much smaller. I assume that…Continue
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Sasha Kapralov liked Capri Granville's blog post 40+ Modern Tutorials Covering All Aspects of Machine Learning40+ Modern Tutorials Covering All Aspects of Machine Learning
This list of lists contains books, notebooks, presentations, cheat sheets, and tutorials covering all aspects of data science, machine learning, deep learning, statistics, math, and more, with most documents featuring Python or R code and numerous illustrations or case studies. All this material is available for free, and consists of content mostly created in 2019 and 2018, by various top experts in their respective fields. A few of these documents are available on LinkedIn: see last section on…See More
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Capri Granville's Blog
40+ Modern Tutorials Covering All Aspects of Machine Learning
Posted on October 12, 2019 at 7:30am 1 Comment 10 Likes
This list of lists contains books, notebooks, presentations, cheat sheets, and tutorials covering all aspects of data science, machine learning, deep learning, statistics, math, and more, with most documents featuring Python or R code and numerous illustrations or case studies. All this material is available for free, and consists of content mostly created in 2019 and 2018, by various top experts in their respective fields. A few of these documents are available on LinkedIn: see last section…
ContinueGIF Image Featuring a Beautiful Visualization
Posted on October 11, 2019 at 6:30am 0 Comments 2 Likes
Free Book: A Comprehensive Guide to Machine Learning (Berkeley University)
Posted on October 3, 2019 at 8:30am 0 Comments 6 Likes
By Soroush Nasiriany, Garrett Thomas, William Wang, Alex Yang. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley. Dated June 24, 2019. This is not the same book as The Math of Machine Learning, also published by the same department at Berkeley, in 2018, and also authored by Garret…
ContinueArtificial Neural Networks in a Nutshell
Posted on September 23, 2019 at 4:30am 0 Comments 2 Likes
According to Wikipedia, an ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron that receives a signal then processes it and can signal neurons connected to it.
In ANN implementations, the "signal" at a connection is a real number, and the output of each neuron is computed by some…
ContinueComment Wall (1 comment)
- At 7:07am on September 22, 2018, aman Ullah said…
Question: A researcher is interested in actual data to research in patterns and build a model for prediction. My question is that if a researcher is interested in actual data why we transform data?
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