A curated list of academic, popular science, and managerial books on Data Mining, Marketing, and Machine Learning.
Read more »Explore data mining methods and gain insight in to how they work and how to analyze the results.
Read more »Get your hands dirty with data wrangling, writing code, and running algorithms on marketing data.
Read more »Summary: Kaggle competitors spend their time exploring the data, building training set samples to build their models on representative data, explore data leaks, and use tools like Python, R, XGBoost, and Multi-Level Models.
Summary: R offers a handful of packages to automate building models. rpart, randomForest, MASS, and forecast packages help you search through a hypothesis space. The caret package helps crawl through the hyper parameter space.
Summary: The passcode riddle asks for three three whole positive numbers with each one being equal to or larger than the next. Turns out there are only a handful of numbers this could possibly work for. Browsing YouTube one morning, I came across the video from TED-Ed and I was intrigued! I’ll be honest, I […]
Summary: Data can be processed in parallel by using multiple threads on a single CPU or by passing code to the data in systems like the Hadoop Distributed File System. Imagine you’re driving your car on the way to work. You keep an eye on the road ahead, the side mirrors, the rearview mirror, and […]
Summary: Before your new analyst arrives, make sure they have access to the data, hardware, and software they’ll need. Set and discuss expectations on what the analyst should know and learn. Get others involved in the development with mentors and formalized “get to know” meetings.
