Top Universities Offering Free Online Programming Courses


https://www.naukri.com/learning/articles/top-universities-offering-free-online-courses-for-programmers/



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From Google and Waymo researchers: The self-/unsupervised revolution is near! Unsupervised optical flow model SMURF improves SOTA by 40% and beats many supervised methods such as PWC-Net and FlowNet2

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SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full-Image Warping

Paper:
https://arxiv.org/pdf/2105.07014.pdf

Video:
https://www.youtube.com/watch?v=W7NCbfZp6QE

Code:
https://github.com/google-research/google-research/tree/master/smurf

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Paper:
https://arxiv.org/pdf/2105.06993.pdf

Project Page:
https://omnimatte.github.io/

Github:
https://github.com/erikalu/omnimatte


Supplimentary material:
https://omnimatte.github.io/supplementary/index.html

Explained:
https://www.youtube.com/watch?v=lCBSGOwV-_o

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Code:
https://github.com/gist-ailab/uoais#unseen-object-amodal-instance-segmentation-uoais

Paper:
https://arxiv.org/abs/2109.11103

Dataset:
https://paperswithcode.com/dataset/ocid

Project page:
https://sites.google.com/view/uoais


join us: @deeplearning_ai

An important collection of the 15 best machine learning cheat sheets.

مجموعة مهمة الافضل ١٥ ورقة غش في مجال التعلم الآلي.

1- Supervised Learning

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf

2- Unsupervised Learning

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf

3- Deep Learning

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-learning.pdf

4- Machine Learning Tips and Tricks

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf

5- Probabilities and Statistics

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf

6- Comprehensive Stanford Master Cheat Sheet

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf

7- Linear Algebra and Calculus

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf

8- Data Science Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf

9- Keras Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf

10- Deep Learning with Keras Cheat Sheet

https://github.com/rstudio/cheatsheets/raw/master/keras.pdf

11- Visual Guide to Neural Network Infrastructures

http://www.asimovinstitute.org/wp-content/uploads/2016/09/neuralnetworks.png

12- Skicit-Learn Python Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf

13- Scikit-learn Cheat Sheet: Choosing the Right Estimator

https://scikit-learn.org/stable/tutorial/machine_learning_map/

14- Tensorflow Cheat Sheet

https://github.com/kailashahirwar/cheatsheets-ai/blob/master/PDFs/Tensorflow.pdf

15- Machine Learning Test Cheat Sheet

https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/

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Summary

Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples.

What's Inside:
* Deep learning from first principles
* Setting up your own deep-learning environment
* Image-classification models
* Deep learning for text and sequences
* Neural style transfer, text generation, and image generation

@Deeplearning_aiDeep Learning with Python (2021)

Invite your friends 🌹🌹
@deeplearning_ai

Deep Learning with Python (2021)

Invite your friends 🌹🌹
@deeplearning_ai