28 thoughts on “A Friendly Introduction to Machine Learning”

  1. 0:05 What is Machine Learning? Humans learn from past experiences, computers learn from previous data.
    2:25 Linear Regression: Finding the line that works best between a given set of points.
    4:10 Gradient Descent : Square of error minimization to get best line fit
    6:20 Detecting Spam e-mails with Naive Bayes Algorithm
    10:35 Decision Tree
    13:20 Logistic Regression
    17:00 Neural network as a logistic regression set intersection
    18:50 Support Vector Machine with linear optimization
    20:05 Kernel trick: planes for curves and vice-versa
    26:00 K-Means clustering
    28:30 Hierarchical Clustering
    29:40 Summary

  2. Damn. By far the best introduction video ever. I was honestly scared after going through many coursera introductory videos. And I was literally on the verge of never looking back into ML. Thanks for this.

  3. I was quite impressed with the way you have explained… its very easy to understand to even a primary students… great work… Please keep uploading such types of interactive videos..

  4. Why? Now I'm interested in machine learning and wants to learn more. Great video with perfect examples.

  5. As someone who has taken an econometrics course (econ major) and now works as a Software Engineer on our NLP pipeline, this helps fill in the bits of knowledge that I'm lacking in machine learning! I didn't even know that's how naive bayes work.

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