Predicting Text Selections with Federated Learning


http://ai.googleblog.com/2021/11/predicting-text-selections-with.html

@Machine_learn

Introducing TensorFlow Graph Neural Networks

A new API for TF2 to build GNNs. It would be interesting to see how it compares to PyG and DGL libraries.
@Machine_learn

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/

@Machine_learn

Machine Learning and AI for Healthcare
#book #AI #ml
@Machine_learn

Periodicity in Cryptocurrency Volatility and Liquidity #Cryptocurrency #Liquidity #Paper @Machine_learn

با عرض سلام دوستانی که نیاز به تهیه ی پکیچ ما دارند می تونن به ایدی بنده پیام بدن @Raminmousa . همچنین دوستانی که نیاز به مشاوره در رابطه با ابده های جدید ، کارهای عملی، پروپوزال و پایان نامه دارند می تونن با ایدی بنده یا شماره واتس اپ بنده 09333900804 در ارتباط باشند.

Deep Learning for disentangling Liquidity-constrained and Strategic Default #DL #Liquidity #Paper @Machine_learn

Deep Neural Networks to Detect Weeds from Crops in Agricultural Environments in Real-Time: A Review

Github: https://github.com/Ildaron/Laser_control

Paper: https://www.mdpi.com/2072-4292/13/21/4486

@Machine_learn

🔹 LUMINOUS: Indoor Scene Generation for Embodied AI Challenges

Github: https://github.com/amazon-research/indoor-scene-generation-eai

Paper: https://arxiv.org/abs/2111.05527v1

Dataset: https://paperswithcode.com/dataset/ai2-thor

@Machine_learn

A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents

Github: https://github.com/extreme-classification/deepxml

Paper: https://arxiv.org/abs/2111.06685v1

Dataset: https://paperswithcode.com/dataset/extreme-classification

@Machine_learn

Improving Vision Transformer Efficiency and Accuracy by Learning to Tokenize


http://ai.googleblog.com/2021/12/improving-vision-transformer-efficiency.html

@Machine_learn

General and Scalable Parallelization for Neural Networks


http://ai.googleblog.com/2021/12/general-and-scalable-parallelization.html

@Machine_learn

🎓 GAN-Supervised Dense Visual Alignment

Github: https://github.com/wpeebles/gangealing

Project: https://www.wpeebles.com/gangealing

Paper: https://arxiv.org/abs/2112.04894v1

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

@Machine_learn

🕷 Bayesian Active Learning (BaaL)

Github: https://github.com/ElementAI/baal

Documentation: https://baal.readthedocs.io.

Paper: https://arxiv.org/abs/2112.06586v1

Blog: https://www.elementai.com/news/2019/element-ai-makes-its-bayesian-active-learning-library-open-source

@Machine_learn

با عرض سلام دوستانی که نیاز به تهیه ی پکیچ ما دارند می تونن به ایدی بنده پیام بدن @Raminmousa . همچنین دوستانی که نیاز به مشاوره در رابطه با ابده های جدید ، کارهای عملی، پروپوزال و پایان نامه دارند می تونن با ایدی بنده یا شماره واتس اپ بنده 09333900804 در ارتباط باشند.

Training Machine Learning Models More Efficiently with Dataset Distillation


http://ai.googleblog.com/2021/12/training-machine-learning-models-more.html

@Machine_learn

Cluster Analysis: Basic Concept #Clustering #book @Machine_learn