I Not too long ago joined ML Zoomcamp to construct my ML expertise.
These are some issues I’ve learnt, I hope you may be taught one thing too.
Week 1:
- What’s Machine Studying ?
Machine studying is the power of machines to select patterns from information and its options, and use the patterns to make predictions to new information.
g(x) ≂ y
- ML VS Rule-Based mostly Methods(RBS)
RBS programs contain you figuring out each doable situation and making a rule for such, this can be a very tedious course of and could be very restricted and time-consuming, these guidelines can as a substitute be used as options to a ML mannequin. The mannequin is skilled on a collected information with these options.
In the sort of ML, a mannequin is skilled on options (x) and their corresponding goal variable (y) or labels.
- CRISP-DM (Cross Business Commonplace Course of for Information Mining)
CRISP is a technique for organizing ML initiatives, it has been round for some time now, previous however nonetheless used. It consists of 6 main steps as proven beneath..
When evaluating fashions in your analysis, watch out, as fashions can get fortunate, so it is advisable to additionally carry out validation and take a look at on every of the fashions you are evaluating to make your best option.
Prepare -> Validate -> Check
Additionally had a numpy, pandas and linear algebra refresher. Then was given an task to bolster all this.
It’s also possible to comply with by way of this repo Ugo’s ML Zoomcamp
