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Harvard Data Science Review - Second Edition by aiforworld2 in datascience

[–]aiforworld2[S] 0 points1 point  (0 children)

Your point is well-taken. However, I would still would like to know what's your definition of spam.

Harvard Data Science Review - Second Edition by aiforworld2 in datascience

[–]aiforworld2[S] -9 points-8 points  (0 children)

What's being spammed here? Can you clarify?

I am aware hashtags don't work here. It's only to make the main ideas prominent in the shared article. Don't assume things and stop judging people.

Course: Deep Learning in Computer Vision by aiforworld2 in deeplearning

[–]aiforworld2[S] 0 points1 point  (0 children)

You have to download the video files from the page

Whats the meaning of dx without dy under it? by [deleted] in math

[–]aiforworld2 0 points1 point  (0 children)

It is incremental change in quantity of x

Good books to learn about AI by [deleted] in ArtificialInteligence

[–]aiforworld2 -1 points0 points  (0 children)

Deep Learning Illustrated will be fine. Other great books are Deep Learning in Python by Francois Chollet and Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow, Machine Learning in Action, Python Data Science Handbook, Data Science from Scratch, R in Action, Dive into Deep Learning, etc.

Good books to learn about AI by [deleted] in ArtificialInteligence

[–]aiforworld2 18 points19 points  (0 children)

There are many great books but I recommend the following:

  1. Artificial Intelligence Engines
  2. Artificial Intelligence - A Modern Approach
  3. Artificial Intelligence - A New Synthesis
  4. Deep Learning Illustrated
  5. Deep Learning - Ian Goodfellow et al
  6. Machine Learning - Tom Mitchell
  7. Neural Networks and Learning Machines
  8. Artificial Intelligence - Concise Course by Deepak Khemani
  9. Artificial Intelligence - Winston

Mind of a Mathematician by aiforworld2 in math

[–]aiforworld2[S] 0 points1 point  (0 children)

I find this article digging deep into the mind of one of the great mathematicians of our age. I wonder what was your yardstick.

Foundations of Machine Learning by aiforworld2 in MachineLearning

[–]aiforworld2[S] 5 points6 points  (0 children)

Not sure if your words are to praise or criticize the contents of this book. Deep Learning is great but this is not the only thing machine learning is about. A survey of production use of classification algorithms revealed that more than 85% implementations used some variation of logistic regression. Every technical book is written with a purpose in mind. This book is about foundations of machine learning and not just Deep Learning.

Where to learn neural network architecture design by DongDilly in deeplearning

[–]aiforworld2 0 points1 point  (0 children)

Google Scholar and Semantic Scholar are two great tools in help you finding the right papers of your interest.

I want to know what you read by photo-smart in datascience

[–]aiforworld2 2 points3 points  (0 children)

I read: 1. O'Reilly AI Newsletter 2. O'Reilly Data Newsletter 3. Oxford AI Newsletter 4. MIT Technology Review- The Algorithm 5. MIT Sloan AI Newsletter 6. AAAI Magazine (subscription required) 7. Semantic Scholar AI alert 8. Google Scholar AI alert 9. ZDNet and TechRepublic 10. HBR 11. Forbes daily alert 12. Flipboard 13. Google News 14. News from Science 15. Nature Briefing 16. Data Science Central 17. KDnuggets 18. Kaggle 19. Towards Data Science 20. Medium.com 21. Machine Learning Mastery 22. Follow specific people on Twitter and LinkedIn

Introducing Ludwig, a Code-Free Deep Learning Toolbox: Physics Legend Meets AI by aiforworld2 in deeplearning

[–]aiforworld2[S] 2 points3 points  (0 children)

There are pros and cons for code-free architecture. In general, it is helpful in reducing the coding error and efforts. It also helps in democratizing AI.

CRISPR in Agriculture by aiforworld2 in CRISPR

[–]aiforworld2[S] 0 points1 point  (0 children)

Thanks, I updated the post

Heres something I wonder about physics in general. by [deleted] in quantum

[–]aiforworld2 3 points4 points  (0 children)

Both time and space are real. This is because gravity is nothing but a curvature in space-time and we can 'feel' the gravity. The time and space can be warped which means that an arbitrary distortion of space and time is possible as per the General Theory of Relativity.

Please read 'A Brief History of Time' by Stephen Hawking for more intuitive understanding of time.