In this full length segment we discuss A/B testing:
Online experimentation is perhaps the most misused of data science techniques. We will walk through the best practices for designing and evaluating A/B and multi-variate tests. We discuss how to choose …
The Amazon ML platform is finely tuned to enable even the most inexperienced data scientist to build and deploy predictive models in the cloud. In this video, we will walk you through creating an AWS account, uploading data into an …
38:22How to automatically web scrape periodically so you can analyze timely/frequently updated data.
There are many blogs and tutorials that teach you how to scrape data from a bunch of web pages once and then you’re done. But one-off web …
01:18:49It’s not hard to see machine learning and artificial intelligence (AI) in nearly every app we use – from any website we visit, to any mobile device we carry, to any goods or services we use.
Where there are commercial …
03:26What is A/B testing? In this quick tutorial, we go over the basics of A/B testing, as well as answer some in-depth questions such as: why should businesses conduct A/B testing? Or how do you perform an A/B test?
Check …
01:05:18In this meetup, Chris Shei talks about the basics of natural language processing: the components of NLP (entities, relations, concepts, semantic roles…), enterprise applications of NLP, and finally build a simple Frequently Asked Questions (FAQ) Chatbot.
About the Speaker:
Chris …
28:14In this final tutorial of our Introduction to dplyr series, we will cover ways to do feature engineering both with dplyr (“mutate” and “transmute”) and base R (“ifelse”). You’ll learn how to impute missing values as well as create new …
13:31We introduce functions that make it easy to find overlapping and distinct values from two different data sources, intersect and setdiff. These two functions let you see the shared and unique elements from different vectors, making it easy to …
13:31We introduce functions that make it easy to find overlapping and distinct values from two different data sources, intersect and setdiff. These two functions let you see the shared and unique elements from different vectors, making it easy to …
21:35We go over some basic functions of dplyr including the mighty group_by and summarize combo that makes dividing up datasets a breeze, as well as arrange, select, and filter that help get the data in a cleaner and more organized …
