Brand-new, hands-on intro to "Big O Notation" — an essential computer science concept. "Big O" allows us to weigh the compute-time vs memory-usage trade-offs of all algorithms, including machine learning models.
This YouTube video is a 45-minute, standalone excerpt from my six-hour "Data Structures, Algorithms, and ML Optimization" course, which focuses on code demos in Python to make understanding concepts intuitive, fun, and interactive.
If you have an O'Reilly Media subscription, the full course was recently published here.
If you'd like to purchase the course, Pearson is offering it this week (until August 28th) at a 70% discount as their "Video Deal of the Week". The URL for this unusually deep discount is here.
This "DSA and ML Optimization" course is the fourth and final quarter of my broader ML Foundations curriculum. All of the associated code is available open-source via GitHub.
Filtering by Tag: dsa
Filming ""Data Structures, Algorithms, and Machine Learning Optimization"" LiveLessons
Silly times on set filming my "Data Structures, Algorithms, and Machine Learning Optimization" videos, which — over 6.5 interactive hours — introduce critical Computer Science concepts for ML and Data Science.
These videos were recently published in the O'Reilly Media platform.
These CS-focused videos are the fourth and final quarter of the subject areas covered in my broader "ML Foundations" curriculum — the first three being Linear Algebra, Calculus, and Probability. All of the code from the curriculum is available open-source in GitHub.
And my "Math for ML" playlist on O'Reilly captures all of the videos in this curriculum in one place.