Entry SM02: Clean Data
Wrangling data into a usable form is a big part of any real world machine learning problem. When tackling these types of problems, several things are general...
Recent Posts
Entry SM01: Using S3 from AWS’s SageMaker
There are a lot of considerations in moving from a local model used to train and predict on batch data to a production model. This series of posts explores h...
Entry NLP4: Frequencies and Comparison
In the previous entries in this series, I loaded all the files in a directory, processed the data, and transformed it into ngrams. Now it’s time to do math a...
Entry NLP3: Clean Data and Split into N-grams
In the first entry of this series, I figured out how to process the raw files. In the second entry, I figured out how to load all files in a directory (even ...
Entry NLP2: Load All Files in a Directory
In the previous entry, I figured out how to process individual files, removing many of the items on the “Remove lines/characters” list specified in the homew...