Hey there! As your friendly language model, I’m here to help proofread and rewrite your text! Here’s the corrected and rewritten version of your post: Let’s do some Machine Learning with SparkR 1.6! The package only gives us the option to do linear or logistic regression, so for this exercise, we’re going to train a…
Let’s talk about SparkR! It’s an R package that provides a lightweight frontend to use Apache Spark from R. I used RStudio and Spark 1.6.1 for this exercise. SparkR has a distributed data frame implementation that supports operations like selection, filtering, and more. Cool, right? In RStudio, run the following code to check the system…
Hey there! Let’s talk about spam filters. You know, those annoying emails that keep showing up in your inbox, even though you never signed up for them. Yeah, those. Well, a spam filter is a program that filters out those unwanted emails and messages. Pretty cool, right? So, we’re going to build and evaluate a…
Alright, folks! The The Analytics Edge course on edX is almost over and boy, have I learned a lot about Machine Learning in the past 2 months! This MOOC is hands down the best one I’ve taken so far, and I hope my other courses can at least live up to its awesomeness. I first…
Hey there, I’m currently knee-deep in a Scala course on Coursera called "Functional Programming in Scala" taught by none other than Martin Ordersky – the inventor of Scala. Let me tell you, creating a Scala ecosystem is no walk in the park. Recently, I hit a roadblock while trying to create an Eclipse project using…
It’s an absolute thrill to be in the top 1% of the Kaggle competition hosted by MIT! This contest is no joke, with some seriously experienced ML implementers throwing their hats into the ring. And let me tell you, the top 3 are on a whole other level – they’ve achieved over 90% accuracy, which…
After diving into regression analysis, I couldn’t wait to test my newfound skills on some real-world data. Luckily, Kaggle has just the thing – they’re hosting a competition called ‘History of Baseball’ and, even better, they’ve provided a dataset for it! I had a blast analyzing Paul dePodesta’s predictions and statistical findings, using linear regression…