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New deep learning course by Andrew Ng

119 points by nilsocket 9y ago

mendeza 9y ago
Is there any past discussions whether these courses will actually get you a job doing deep learning? I am skeptical these courses would get you a job in deep learning.
nilsocket 9y ago
Here is the link to the coursera web-page: https://www.coursera.org/specializations/deep-learning https://www.coursera.org/specializations/deep-learning In-short this specialization covers: 1.Neural Networks 2.Hyperparameter tuning, Regularization and Optimization 3.Structuring Machine Learning Projects 4.Convolutional Neural Networks 5.Sequence Models
Sjenk 9y ago
It says it is free to audit the videos, but I can only find a button that lets me enroll for free for 7 days before paying $49 a month. Am I missing something? EDIT: nevermind when you click enroll then there is a small text in the left bottom of the pop up thats says audit the course.
- wichert 9y ago
  Did they remove that link? I can't find it anywhere.
  - rcdmd 9y ago
    Click enroll, then look in the bottom left corner of the popup modal.
    - bauerd 9y ago
      There's only the "Start Free Trial" button for me
      - urlwolf 9y ago
        They seem to have removed the 'audit course' option, at least on my setup. They may be doing AB testing.
      - cicero19 9y ago
        If you click the Enroll button on this link you will find the Audit link: https://www.coursera.org/learn/neural-networks-deep-learning https://www.coursera.org/learn/neural-networks-deep-learning
  - redsymbol 9y ago
    There's a trick to making it appear. See my other comment in this discussion.
deleted 9y ago
[deleted]
binarymax 9y ago
I'm taking this class now. I've finished the first two weeks of the first course and am about to begin the first set of programming assignments. Some initial impressions: - I really like Andrews teaching style, which is why I took the course. If you are familiar with his machine learning coursera class and enjoy it, you will enjoy this as well. It really feels like a seamless continuation of the ML course and the concepts taught there are helpful. You may want to go through that course first to learn the basics, but if your math is solid you can jump right in to this. - the course teaches python, numpy, and tensorflow. Some folks had trouble with Octave in the ML course, so many will appreciate the stack being taught here. - there is lots of foundational mathematics. Some like that (I do) and some don't. If you are not interested in core calculus or linear algebra details and just want to learn applied deep learning through code, you may enjoy the fast.ai courses more (which to me felt a bit cargo culty) - it's still early in the specialization for me so take the above with a grain of salt!
- Edd314159 9y ago
  Do you know of any courses that will bring one up to speed on the math component? I really love this format of learning, and I want to take this course as it's something I'm interested in and I like Andrew Ng, but the Week 2 content was a complete non-starter for me. I've been writing software professionally for a decade now, but because I have no mathematical background I'm very far from understanding even the first step of this course (which really is Week 2, Week 1 is just a formality).
  - sonabinu 9y ago
    Get familiar with linear algebra. What I did was go back to school ( community college for cal2, linear algebra, differential equations and multi-variable calculus. ) I'm comfortable with the math now. It's a commitment for about a year but really worth your time.
  - imakecomments 9y ago
    Audit edx's Calculus sequence, taught by MIT. The courses are: Calculus 1A, 1B, 1C. You can watch MIT OCW's Linear Algebra course with Strang and/or enroll in: "Linear Algebra - Foundations to Frontiers" on edx. Use Khan academy for supplemental Calculus & Linear Algebra review. You can get Stewart's Calculus text and read through it/attempt the problem sets. Once you have a solid Calculus/Linear Algebra review you can take a look at: "Statistics 110: Probability" which is found free here: https://projects.iq.harvard.edu/stat110/home https://projects.iq.harvard.edu/stat110/home.
brudgers 9y ago
News discussion, https://news.ycombinator.com/item?id=14958779 https://news.ycombinator.com/item?id=14958779
redsymbol 9y ago
At first I could not find a way to sign up without paying - when I click enroll, I didn't see the audit link that Sjenk and others mention. The trick is that the audit link only appears when you sign up for the individual course, not the entire sequence. So if you go to this link: https://www.coursera.org/specializations/deep-learning https://www.coursera.org/specializations/deep-learning ... and click "Enroll", you can only proceed by supplying payment info. However, if you scroll down to that page to the box titled "Course 1", at the bottom of that box is a link "You can choose to take this course only. Learn More". Click on THAT to go to the individual course page. Then, click Enroll, and in the first box that pops up, you'll see the link "Or audit this course" in the lower left. This allowed me to sign up for all five without supplying payment info.
- chairmankaga 9y ago
  To add to that, I couldn't make it work following these steps, but logging out and following the steps above worked for me. Thanks.
- Torai 9y ago
  But you can't submit exercises. https://learner.coursera.help/hc/en-us/articles/209818613-Enrollment-options https://learner.coursera.help/hc/en-us/articles/209818613-En... When you audit a course: - You'll be able to see most of the course materials for free, but you won't be able to submit certain assignments or get grades for your work. - You won't be able to submit assignments for feedback or a grade. - You won't get a Course Certificate.
  - Blackthorn 9y ago
    Ugh, Coursera has gone way downhill.
    - sgslo 9y ago
      Its a business, do you not expect them to somehow collect revenue on products they have created?
2_listerine_pls 9y ago
Now right it taking.
SoMisanthrope 9y ago
I'm pretty excited about this... at work, we are using machine learning to train models that allow us to automate the process of grading student essays. The product is called LightSide. I hope to apply my learning from the class to improving our models and our scoring accuracy. Woowhoo, thanks Dr. Ng!
- WoodenChair 9y ago
  I would be furious if my essay was graded by a computer. Is the model really good enough to account for all the variances in human language? Is the whole thing graded automatically or just the grammar?
  - damvigilante 9y ago
    I don't know about the specific project SoMisanthrope is talking about, but these types of tools are often used in conjunction with human graders. e.g. Instead of having 2 human graders, you automate the grading and have 1 human grader, and if the grades differ by some amount, only then do you bring in a secondary grader.
    - SoMisanthrope 9y ago
      Good point DamVigilante. We trained the model using hundreds of human-scored essays. They were all double or triple scored, to validate IRR. I think that's why the model is performing so well. But, there is always room for improvement! :-)
  - SoMisanthrope 9y ago
    I hear you WoodenChair. For this particular task, the stakes are very low (really, zero). The model agrees with our human graders, quite well. In fact, statistically speaking, the machine scoring is actually tightly correlated to the highest inter-rater reliability that we could achieve, among our human graders. You would be surprised.
dannysu 9y ago
There are several courses in this specialization. Only 3 are currently available for enrollment right now. You can get the course material for free, but won't be able to get assignments graded. Below are links for all of the courses. Course 1: https://www.coursera.org/learn/neural-networks-deep-learning https://www.coursera.org/learn/neural-networks-deep-learning Course 2: https://www.coursera.org/learn/deep-neural-network https://www.coursera.org/learn/deep-neural-network Course 3: https://www.coursera.org/learn/machine-learning-projects https://www.coursera.org/learn/machine-learning-projects Course 4: https://www.coursera.org/learn/convolutional-neural-networks https://www.coursera.org/learn/convolutional-neural-networks Course 5: https://www.coursera.org/learn/nlp-sequence-models https://www.coursera.org/learn/nlp-sequence-models To get the course material, you go to each course link and click on "Enroll". Then look for the "Audit" link at the bottom left of the modal dialog that comes up.

119 points by nilsocket 9y ago

Is there any past discussions whether these courses will actually get you a job doing deep learning? I am skeptical these courses would get you a job in deep learning.

nilsocket 9y ago

Here is the link to the coursera web-page: https://www.coursera.org/specializations/deep-learning https://www.coursera.org/specializations/deep-learning In-short this specialization covers: 1.Neural Networks 2.Hyperparameter tuning, Regularization and Optimization 3.Structuring Machine Learning Projects 4.Convolutional Neural Networks 5.Sequence Models

Sjenk 9y ago

It says it is free to audit the videos, but I can only find a button that lets me enroll for free for 7 days before paying $49 a month. Am I missing something? EDIT: nevermind when you click enroll then there is a small text in the left bottom of the pop up thats says audit the course.

wichert 9y ago
Did they remove that link? I can't find it anywhere.
- rcdmd 9y ago
  Click enroll, then look in the bottom left corner of the popup modal.
  - bauerd 9y ago
    There's only the "Start Free Trial" button for me
    - urlwolf 9y ago
      They seem to have removed the 'audit course' option, at least on my setup. They may be doing AB testing.
    - cicero19 9y ago
      If you click the Enroll button on this link you will find the Audit link: https://www.coursera.org/learn/neural-networks-deep-learning https://www.coursera.org/learn/neural-networks-deep-learning
- redsymbol 9y ago
  There's a trick to making it appear. See my other comment in this discussion.

deleted 9y ago

[deleted]

binarymax 9y ago

I'm taking this class now. I've finished the first two weeks of the first course and am about to begin the first set of programming assignments. Some initial impressions: - I really like Andrews teaching style, which is why I took the course. If you are familiar with his machine learning coursera class and enjoy it, you will enjoy this as well. It really feels like a seamless continuation of the ML course and the concepts taught there are helpful. You may want to go through that course first to learn the basics, but if your math is solid you can jump right in to this. - the course teaches python, numpy, and tensorflow. Some folks had trouble with Octave in the ML course, so many will appreciate the stack being taught here. - there is lots of foundational mathematics. Some like that (I do) and some don't. If you are not interested in core calculus or linear algebra details and just want to learn applied deep learning through code, you may enjoy the fast.ai courses more (which to me felt a bit cargo culty) - it's still early in the specialization for me so take the above with a grain of salt!

Edd314159 9y ago
Do you know of any courses that will bring one up to speed on the math component? I really love this format of learning, and I want to take this course as it's something I'm interested in and I like Andrew Ng, but the Week 2 content was a complete non-starter for me. I've been writing software professionally for a decade now, but because I have no mathematical background I'm very far from understanding even the first step of this course (which really is Week 2, Week 1 is just a formality).
- sonabinu 9y ago
  Get familiar with linear algebra. What I did was go back to school ( community college for cal2, linear algebra, differential equations and multi-variable calculus. ) I'm comfortable with the math now. It's a commitment for about a year but really worth your time.
- imakecomments 9y ago
  Audit edx's Calculus sequence, taught by MIT. The courses are: Calculus 1A, 1B, 1C. You can watch MIT OCW's Linear Algebra course with Strang and/or enroll in: "Linear Algebra - Foundations to Frontiers" on edx. Use Khan academy for supplemental Calculus & Linear Algebra review. You can get Stewart's Calculus text and read through it/attempt the problem sets. Once you have a solid Calculus/Linear Algebra review you can take a look at: "Statistics 110: Probability" which is found free here: https://projects.iq.harvard.edu/stat110/home https://projects.iq.harvard.edu/stat110/home.

brudgers 9y ago

News discussion, https://news.ycombinator.com/item?id=14958779 https://news.ycombinator.com/item?id=14958779

redsymbol 9y ago

At first I could not find a way to sign up without paying - when I click enroll, I didn't see the audit link that Sjenk and others mention. The trick is that the audit link only appears when you sign up for the individual course, not the entire sequence. So if you go to this link: https://www.coursera.org/specializations/deep-learning https://www.coursera.org/specializations/deep-learning ... and click "Enroll", you can only proceed by supplying payment info. However, if you scroll down to that page to the box titled "Course 1", at the bottom of that box is a link "You can choose to take this course only. Learn More". Click on THAT to go to the individual course page. Then, click Enroll, and in the first box that pops up, you'll see the link "Or audit this course" in the lower left. This allowed me to sign up for all five without supplying payment info.

chairmankaga 9y ago
To add to that, I couldn't make it work following these steps, but logging out and following the steps above worked for me. Thanks.
Torai 9y ago
But you can't submit exercises. https://learner.coursera.help/hc/en-us/articles/209818613-Enrollment-options https://learner.coursera.help/hc/en-us/articles/209818613-En... When you audit a course: - You'll be able to see most of the course materials for free, but you won't be able to submit certain assignments or get grades for your work. - You won't be able to submit assignments for feedback or a grade. - You won't get a Course Certificate.
- Blackthorn 9y ago
  Ugh, Coursera has gone way downhill.
  - sgslo 9y ago
    Its a business, do you not expect them to somehow collect revenue on products they have created?

2_listerine_pls 9y ago

Now right it taking.

SoMisanthrope 9y ago

I'm pretty excited about this... at work, we are using machine learning to train models that allow us to automate the process of grading student essays. The product is called LightSide. I hope to apply my learning from the class to improving our models and our scoring accuracy. Woowhoo, thanks Dr. Ng!

WoodenChair 9y ago
I would be furious if my essay was graded by a computer. Is the model really good enough to account for all the variances in human language? Is the whole thing graded automatically or just the grammar?
- damvigilante 9y ago
  I don't know about the specific project SoMisanthrope is talking about, but these types of tools are often used in conjunction with human graders. e.g. Instead of having 2 human graders, you automate the grading and have 1 human grader, and if the grades differ by some amount, only then do you bring in a secondary grader.
  - SoMisanthrope 9y ago
    Good point DamVigilante. We trained the model using hundreds of human-scored essays. They were all double or triple scored, to validate IRR. I think that's why the model is performing so well. But, there is always room for improvement! :-)
- SoMisanthrope 9y ago
  I hear you WoodenChair. For this particular task, the stakes are very low (really, zero). The model agrees with our human graders, quite well. In fact, statistically speaking, the machine scoring is actually tightly correlated to the highest inter-rater reliability that we could achieve, among our human graders. You would be surprised.

dannysu 9y ago

There are several courses in this specialization. Only 3 are currently available for enrollment right now. You can get the course material for free, but won't be able to get assignments graded. Below are links for all of the courses. Course 1: https://www.coursera.org/learn/neural-networks-deep-learning https://www.coursera.org/learn/neural-networks-deep-learning Course 2: https://www.coursera.org/learn/deep-neural-network https://www.coursera.org/learn/deep-neural-network Course 3: https://www.coursera.org/learn/machine-learning-projects https://www.coursera.org/learn/machine-learning-projects Course 4: https://www.coursera.org/learn/convolutional-neural-networks https://www.coursera.org/learn/convolutional-neural-networks Course 5: https://www.coursera.org/learn/nlp-sequence-models https://www.coursera.org/learn/nlp-sequence-models To get the course material, you go to each course link and click on "Enroll". Then look for the "Audit" link at the bottom left of the modal dialog that comes up.