When building a machine learning model, it’s important to measure the results of your model. Typically, you split a dataset into a training dataset and a test dataset. The training dataset is used to train your model, while the test dataset is used to measure the performance of your model. A commonly used method to […]
Category: Data Science
Tuning / regularizing common linear regressions and classifiers in scikitlearn
If you read my article in January about my personal development goals, you might have seen that I’m working to achieve the DP-200 certification. During the learning process for DP-200, I learned that I lacked certain basic knowledge about how to do data engineering / data science in Python. For that reason, I decided to […]
Using Form Recognizer to recognize custom forms
One of my learning goals for this half year was to learn more about AI. Although I’m focusing my learning mainly on low-level AI (Python, ML, Data Science), I was pretty happy to get involved in a customer project using the Microsoft Form Recognizer. This blog post will cover the Form Recognizer and it’s functionality. […]
Book review: Weapons of math destruction
I just spent a week of vacation in Italy. One of my good friends from college was getting married, and I didn’t want to miss his wedding. It was a good time for Kelly (my wife) and I to also take a week of vacation prior to the wedding. We love Italy, and a wedding […]
Exploring the DP-100 certification path
For the past couple of months, learning more about AI and data science has been on my learning backlog. However, I never actually sat down and put down a plan for learning. The way I like to learn, is by setting myself a challenge. Just subscribing to a course, or setting the goal of learning […]