If you want to get the lowdown on Coursera’s Machine Learning course in one place, then you’ll LOVE this review.
Just curious about machine learning or this course, you’ll love this review, too! 🙂
I personally took the course and reviewed the course structure, logistics, assignments and much more.
Check it out!
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One month ago, I got an email from a colleague:
The subject of his email was a single word: PyData
The email had a single EventBrite.com URL.
Intrigued, I clicked… and that’s when my adventure into PyData began.
In this post, I’m going to take you through 3 of the tutorials at PyData Seattle 2015: Simulation, PySpark and Deep Learning.
Continue reading “PyData Seattle 2015 – Simulation, PySpark and Deep Learning Tutorials”
Knowing the top 10 most influential data mining algorithms is awesome.
Knowing how to USE the top 10 data mining algorithms in R is even more awesome.
That’s when you can slap a big ol’ “S” on your chest…
…because you’ll be unstoppable!
Today, I’m going to take you step-by-step through how to use each of the top 10 most influential data mining algorithms as voted on by 3 separate panels in this survey paper.
By the end of this post…
You’ll have 10 insanely actionable data mining superpowers that you’ll be able to use right away.
Continue reading “Top 10 data mining algorithms in plain R”
Today, I’m going to explain in plain English the top 10 most influential data mining algorithms as voted on by 3 separate panels in this survey paper.
Once you know what they are, how they work, what they do and where you can find them, my hope is you’ll have this blog post as a springboard to learn even more about data mining.
What are we waiting for? Let’s get started!
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Data mining is everywhere, but its story starts many years before Moneyball and Edward Snowden. The following are major milestones and “firsts” in the history of data mining plus how it’s evolved and blended with data science and big data.
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Highly effective data analysis isn’t learned overnight, but it can be learned faster. Here are 7 habits of data analysis I wish someone told me for effectively incorporating, communicating and investing in data analysis geared towards an engineering team.
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Learning R is easier if you can apply it to a real-world problem. Broken links are a problem for anyone who owns or maintains their own website. In this video series, I’ll step through an analysis of a broken links dataset using R.
Continue reading “Data analysis example – Broken link checking”
I’m building a free online resource for R on top of my personal blog over at EverydayR.com. The basic idea is to share, learn and explore R together. Hopefully, we’ll both come out better. 🙂
Continue reading “Installing R and RStudio”
You’ve found a few broken links on your blog or web site, and now you wonder whether there are more. Here’s a quick way to get a sense of how big the problem is.
Continue reading “Broken link checker analysis with R”
In two previous posts (intro, data entry), I described a simple, quick and easy solution for recording newborn feedings, dirty diapers and just about anything of interest. Here’s the second part of the implementation: the data analysis.
Continue reading “Newborn app using Twitter and R (data analysis)”