dimreductiontechniquespydatadcoct2016.pdf
1.2 MB
A Practical Guide to Dimensionality Reduction Techniques
If you start reading Fastbook
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Deep Learning with PyTorch Step-by-Step
Notebooks
use βOpen in Colabβ extention in your browser to execute online.
Notebooks
use βOpen in Colabβ extention in your browser to execute online.
decorators.pdf
55.8 KB
π2
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π2
"Information Theory: From Coding to Learning"
coming out soon: 600+ pages with 150+ exercises
by Y. Polyanskiy and Y. Wu
Cambridge University Press
https://people.lids.mit.edu/yp/homepage/papers.html
book draft
coming out soon: 600+ pages with 150+ exercises
by Y. Polyanskiy and Y. Wu
Cambridge University Press
https://people.lids.mit.edu/yp/homepage/papers.html
book draft
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www.perplexity.ai
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Linkes inside the answer works correctly.
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π€©1
High-Performance Computing with Python
The course covers the following topics:
- Vectorization with NumPy and the SciPy stack
- Profiling python code
- Extending python with cython, cffi and f2py
- Just-in-time compilation with numba
- Distributed-memory parallel programming with python
- Interfaces to GPUs
GitHub
Video 1
Video 2
Video 3
The course covers the following topics:
- Vectorization with NumPy and the SciPy stack
- Profiling python code
- Extending python with cython, cffi and f2py
- Just-in-time compilation with numba
- Distributed-memory parallel programming with python
- Interfaces to GPUs
GitHub
Video 1
Video 2
Video 3
GitHub
GitHub - eth-cscs/PythonHPC: PythonHPC
PythonHPC. Contribute to eth-cscs/PythonHPC development by creating an account on GitHub.