Computer Science and Programming

2022-03-11 13:24:52 Reading suggestions to keep you up-to-date with the latest and classic breakthroughs in AI and Data Science.

https://towardsdatascience.com/ai-papers-to-read-in-2022-c6edd4302247 Open / Comment

2022-02-21 15:09:15 A lightweight vision library for performing large scale object detection & instance segmentation

Github: https://github.com/obss/sahi

Paper: https://arxiv.org/abs/2202.06934v1

Kaggle notebook: https://www.kaggle.com/remekkinas/sahi-slicing-aided-hyper-inference-yv5-and-yx

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

@computer_science_and_programming Open / Comment

2022-01-30 20:37:22 323+ Open Source Pytorch Implementation Software Projects
Free and open source pytorch implementation code projects including engines, APIs, generators, and tools.

https://opensourcelibs.com/libs/pytorch-implementation

A curated list of tutorials, papers, projects, communities and more related to PyTorch:

https://www.ritchieng.com/the-incredible-pytorch/

https://github.com/ritchieng/the-incredible-pytorch


@computer_science_and_programming Open / Comment

2022-01-18 05:00:08 Uniformer: Unified Transformer for Efficient Spatiotemporal Representation Learning

Github: https://github.com/sense-x/uniformer

Paper: https://arxiv.org/abs/2201.04676v1

Tasks: https://paperswithcode.com/dataset/kinetics-600

@computer_science_and_programming Open / Comment

2022-01-09 23:43:54 An important collection of the 15 best machine learning cheat sheets.

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/

@computer_science_and_programming Open / Comment

2021-12-31 23:11:42 Happy new year
Thank you for being with us
We appreciate your patience to science and always try to provide best content for subscribers Open / Comment

2021-12-23 08:45:08 Page: https://d2l.ai/

PyTorch based: https://d2l.ai/d2l-en-pytorch.pdf

MXNET based: https://d2l.ai/d2l-en.pdf

Github: https://github.com/d2l-ai/d2l-en

@computer_science_and_programming Open / Comment

2021-12-23 08:45:06 Dive into Deep Learning

Interactive deep learning book with code, math, and discussions

Implemented with NumPy/MXNet, PyTorch, and TensorFlow

Adopted at 300 universities from 55 countries Open / Comment

2021-12-10 11:14:48 OBJECT-AWARE CROPPING FOR SELF-SUPERVISED LEARNING

Paper:
https://arxiv.org/pdf/2112.00319v1.pdf

Github:
https://github.com/shlokk/object-cropping-ssl

@computer_science_and_programming Open / Comment

2021-12-10 11:14:04 Object-aware cropping, a simple, fast and highly effective data augmentation alternative to random scene cropping for SELF-SUPERVISED LEARNING Open / Comment