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Hey, there are many paths into the field of machine learning and most start with theory.
A strategy for getting started and practicing the skill of applied machine learning is to design and execute small projects.
The projects are:
* Small in time (about 5-10 hours).
* Small in scope (focus on one learning outcome).
* Small in resources (your PC and open source software).
The objective of a small project is to learn one thing. With this approach, you can use to very quickly build up practical skills
in machine learning.
Small projects are small in a few dimensions to ensure that they completed and that you extract the learning benefits and move
onto the next project.
There are 4 types of small projects I suggest:
1. Study a machine learning tool
2. Study a machine learning dataset
3. Study a machine learning algorithm
4. Implement a machine learning algorithm
Learn more about small projects in the post:
>> 4 Self-Study Machine Learning Projects
I'll speak to you soon.
Jason.
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