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This course has been a broad overview of machine learning. We looked at a lot of big ideas and we even explored some code. Let's do a quick review.
Further Reading
- Ethical Design: Treehouse course - Stage 3, in particular, covers machine learning.
This course has been a broad
overview of machine learning.
0:00
We looked at a lot of big ideas and
we even exported some code.
0:04
Let's do a quick review.
0:09
Machine Learning is a new approach
to artificial intelligence.
0:11
With an emphasis on statistical analysis,
and the ability for the computer to write
0:16
its own set of rules, rather than humans
writing all of the conditional logic.
0:21
There are two major categories of
Machine Learning, Supervised Learning and
0:27
Unsupervised Learning.
0:32
Supervised learning is when a machine
intelligence predicts a category or
0:33
a quantity using models of classification
and regression respectively.
0:38
Unsupervised learning is when
a computer analyzes unlabeled data and
0:44
attempts to recognize patterns.
0:48
The most common unsupervised models use
0:51
clustering to group
similar things together.
0:53
When handling data, remember that an
example is a single element in a dataset.
0:57
And a feature is one
characteristic of an example.
1:03
These basic models can lead to more
complex and emerging behaviors in specific
1:07
domains like chatbots, image recognition,
speech recognition and more.
1:12
More specialized applications like this
can be served by higher level machine
1:19
learning platforms including AWS and
IBM Watson.
1:23
If you didn't understand everything,
don't worry.
1:29
That's normal.
1:32
I encourage you to watch this course
again, explore the teacher notes,
1:33
and look at the documentation for
scikit-learn.
1:37
You may also want to try exploring
more problems using scikit-learn.
1:41
See if you can apply classification
to another data set.
1:46
Or try something more advanced
like regression or clustering.
1:50
With more practice and
1:55
repetition, your understanding will
grow and you'll be ready for more.
1:56
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