Lecture 1 | Machine Learning (Stanford)

Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng provides an overview of the course in this introductory meeting.

This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed.

Complete Playlist for the Course:

CS 229 Course Website:

Stanford University:

Stanford University Channel on YouTube:

30 comments

  1. Roshan Mathew says:

    Watching this today — 10 june 2017 , nine years after upload , need to search youtube for similar future relevant videos uploaded this year 2017 . to avoid watching them 10 years later.

  2. Charles Brightman says:

    Learn how to eternally consciously exist, somehow, someway, somewhere, in some state of existence, for without an actual eternal conscious existence throughout all of future eternity, all else is ultimately meaningless because one day it will all be forgotten as there will not be a conscious entity left to eternally care. All of life itself would just be an illusion, an illusion that will end one day and be forgotten.

    This Earth is supposedly entering into the sixth mass extinction event.
    Modern science claims this Earth and our Sun will not last for literally all of future eternity.
    I personally believe our solar system is being pulled toward our galactic center’s black hole and also is why our galaxy is spiral shaped.

    Put machine learning in how to consciously survive beyond this Earth and solar system, and possibly the galaxy as well. Otherwise, all else is ultimately meaningless.
    (Of which main stream modern science believes this universe will end in a “big freeze”, “big crunch” or by some other means. I am in the minority with my learning that they might be wrong. But, we would still have to get off of this Earth and out of this solar system, and either be able to move about this galaxy or be able to leave it one day.)
    And “if” modern science is right concerning the end of this universe, then put that machine learning in how to party like there is no tomorrow, because one day, it will be really true.
    (OSICA)

  3. Charles Brightman says:

    Artificial Intelligence and Machine Learning:
    In essence, a consciousness is being created, a consciousness that has basic conscious choices:
    Help, Neutral, Hurt and to whom to Help, Neutral, Hurt.

    And “it”, along with other artificial intelligence machines, along with biological individual conscious species, will still just be an individual in a society of individuals. Conscious individuals with choices as stated above. “IF” focused on an individual, which individual? “IF” focused on a larger society of individuals, which larger society of individuals?

    What is “best” for an individual may or may not be what is “best” for a larger society of individuals, and conversely, what is “best” for a larger society of individuals may or may not be what is “best” for the individual. But, we are individuals in a society of individuals while we consciously exist, so what exactly are the choices we, individually and as a larger society of individuals, choose?

    And if none of us actually eternally consciously exist throughout all of future eternity, does it all matter anyway what any of us choose? Whose eternally consciously left to care?

  4. Charles Brightman says:

    Artificial intelligence and big data:
    While they may know a lot, they too don’t know what they don’t know.
    Missing even one pertinent fact and/or not correctly understanding even one pertinent fact and/or not correctly connecting two or more pertinent facts properly together, and wrong conclusions could be reached. Even dangerous and deadly conclusions. Hopefully they consciously live long enough to learn from their own and other’s mistakes. Otherwise, they too will consciously die one day from something, forget everything they ever knew and experienced, and will be forgotten, just like the rest of us. (Of which, even if they had all the knowledge, understanding, wisdom and applications of “God” but one, to have an actual eternal conscious existence throughout all of future eternity, even they would cease to consciously exist one day, forget everything, and be forgotten. Even their very own existence and all that they may have done and/or not done, would all be ultimately meaningless in the grandest scheme of things.)
    (OSICA)

  5. Charles Brightman says:

    “Eternal conscious existence throughout all of future eternity” = “Good dog”.
    (But then, what to do with that eternal conscious existence?)
    “No eternal conscious existence throughout all of future eternity” = “Bad dog”.
    (Does not matter that the dog even exists, much less whatever it does and/or doesn’t do.)

  6. Somit Sinha says:

    (around 01:04:04) why do we assume that over time beings would learn to do stuffs which fetch them a positive reward ?

  7. Anshuman Rohella says:

    Thank you Stanford for putting these lectures up on youtube. I feel so fucking lucky to watch these. #KnowledgeISPower

  8. Chaeun Lee says:

    The books recommended on the CS229 site are , I think, a little bit old version. So, I suppose you refer the following books. They will be helpful.

    Fundamentals and review for the lectures
    1. Pattern classification and machine learning

    Covers recent trends and fundamentals
    2. Deep Learning, MIT press

    Mathematically rigorous
    3. Understanding machine learning theory algorithms, Cambridge Univ. Press

    I, also, cannot see these books perfectly, but I convince that they will be good references.

    Thank you, Prof Andrew Ng.

  9. AllTheBest Fails says:

    Just wanted to point out how he says that matlab is better than R. Its 2017 now, and R is arguably better than matlab on so many levels…. Of course no one can see the future, not even the smartest person. These lectures are awesome, and we live in a time where we can find all the human knowledge, even thousands of years old, just in few seconds anywhere on earth. how amazing is that!

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