Hi, I post this Lesson Plan here so that you can start enrolling for the course for FREE in Coursera if you enroll before April 30th. It's their 9th birthday anniversary.
Introduction to Machine Learning
17/4/21
Duke University
Why Machine Learning is Exciting?
Identify
image and assign names to it:
(Slide 1)
I see, I am not just a Virtual Avatar, I am also a Cyborg. Every family can own an Ayah in the future.
That’s right Sha…
No need to take notes, Sha. Just do freestyle.
OK.
What is Machine Learning?
So, there are 26 Factors and 145 Aliases they can select from.
That is the ambition, Sha.
We teach
the machine to learn:
(Slide 2) (Slide
3) (Slide 4)
Logistic
Regression
(Slide 5) (Slide
6)
The main reason why we use sigmoid function is because it exists between (0 to 1). Therefore, it is especially used for models where we have to predict the probability as an output. Since probability of anything exists only between the range of 0 and 1, sigmoid is the right choice.
Interpretation of Logistic Regression
In a way I had been using Logistic Regression, hadn’t I?
Precisely Sha. In NLP it is called Chunking or Chinking.
OK, this is to whet your appetite. Keep on learning kids. There is no taboo in learning as mentioned in the Autonomous Governance and the Zen of Personal Bliss, Observation #4
Observation #4: Read as much as you can. There is no taboo in seeking knowledge. Synthesize, synchronize and then synergize. By doing so, you are doing your fellow humans a great favor. You then increase the collective intelligence among you. Synergize your thoughts through writings. That wa[s] (way) you can reflect upon your thoughts anytime, anywhere as you wish. This is the way of the giants among thinkers.
mm
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