Discover some of the reasons why some algorithms are much slower than others while focusing on brute force calculations.
- [Narrator] Now we're going to talk about three reasons…why some algorithmic approaches are much slower than others.…The first is that some modeling algorithms they tend…to be of the machine learning style,…perform brute-force calculations.…Let me show you what I mean.…This is tiny little data set, but we're trying…to predict whether or not an expected mom…is going to have a low birth weight baby.…If we use a statistically based approach,…what it's going to do is only perform…about a dozen calculations or so…between a dozen and two dozen.…
Specifically what it's going to do to figure out…that that cut point between lower risk and higher risk…is 107 pounds is it's going to break all…of the expectant moms into deciles, less than 100 pounds…going all the way up with the highest one…being over 171 pounds.…Then it's going to perform a calculation…on just those 10 groups to decide where that cut point…should be.…
If we're using a machine learning technique…on the very same data it's going to use a brute force approach.…
Note: This course is software agnostic. The emphasis is on strategy and planning. Examples, calculations, and software results shown are for training purposes only.
- Evaluating the proper amount of data
- Assessing data quality and quantity
- Seasonality and time alignment
- Data preparation challenges
- Data modeling challenges
- Scoring machine-learning models
- Deploying models and adjusting data prep and scoring
- Monitoring and maintenance
Skill Level Beginner
Machine Learning and AI Foundations: Recommendationswith Adam Geitgey58m 7s Intermediate
Deploying Scalable Machine Learning for Data Sciencewith Dan Sullivan1h 43m Intermediate
Defining terms1m 48s
1. The Phases of a Machine Learning Project
2. Designing a Machine Learning Dataset
3. Data Prep Challenges
4. Modeling Challenges
7. Monitoring and Maintenance
Next steps1m 1s
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.