Awesome news for beginners in #MachineLearning and #DeepLearning
We've all come to love Dr. Strang's Linear Algebra Lectures from MIT. But his books are sometimes expensive for students and also not available.
Now Stanford University changed all that with their free book they released called "Introduction to Applied Linear Algebra" written by Stephen Boyd and Lieven Vandenberghe
Go get them all here on my #Github page, I will create some beginners lectures and #Python & #Julia notebooks there soon.
Root / main folder: https://lnkd.in/de8uepd
1. The 473 page book itself: https://bit.ly/2tjFNdA
2. Lovely Julia language companion book worth 170 pages! : https://bit.ly/2BxYGy0
3. Exercises book: https://bit.ly/2RZoVTf
4, Course lecture slides: https://bit.ly/2N9TZPC
#beginner #datascience #learning #machinelearning
@kdnuggets @datasciencechats
Source: Linkedin - Tarry Singh
We've all come to love Dr. Strang's Linear Algebra Lectures from MIT. But his books are sometimes expensive for students and also not available.
Now Stanford University changed all that with their free book they released called "Introduction to Applied Linear Algebra" written by Stephen Boyd and Lieven Vandenberghe
Go get them all here on my #Github page, I will create some beginners lectures and #Python & #Julia notebooks there soon.
Root / main folder: https://lnkd.in/de8uepd
1. The 473 page book itself: https://bit.ly/2tjFNdA
2. Lovely Julia language companion book worth 170 pages! : https://bit.ly/2BxYGy0
3. Exercises book: https://bit.ly/2RZoVTf
4, Course lecture slides: https://bit.ly/2N9TZPC
#beginner #datascience #learning #machinelearning
@kdnuggets @datasciencechats
Source: Linkedin - Tarry Singh
GitHub
Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials/Beginners_Guide_Math_LinAlg/Applied Linear Algebra at master ·…
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas ...
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Want to jump ahead in artificial intelligence and/or digital pathology? Excited to share that after 2+ years of development PathML 2.0 is out! An open source #computational #pathology software library created by Dana-Farber Cancer Institute/Harvard Medical School and Weill Cornell Medicine led by Massimo Loda to lower the barrier to entry to #digitalpathology and #artificialintelligence , and streamline all #imageanalysis or #deeplearning workflows.
⭐ Code: https://github.com/Dana-Farber-AIOS/pathml
⭐ Code: https://github.com/Dana-Farber-AIOS/pathml
GitHub
GitHub - Dana-Farber-AIOS/pathml: Tools for computational pathology
Tools for computational pathology. Contribute to Dana-Farber-AIOS/pathml development by creating an account on GitHub.
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