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Machine learning books and papers
2_5361938490604913448.pdf
4.3 MB
Learning Scrapy Learn the art of efficient web scraping and crawling with Python
#book #python #Scrapy
@Machine_leaen
4.06K views
Machine learning books and papers
@Machine_learn
​​New paper on training with pseudo-labels for semantic segmentation

Semi-Supervised Segmentation of Salt Bodies in Seismic Images:
SOTA (1st place) at TGS Salt Identification Challenge.

Github: https://github.com/ybabakhin/kaggle_salt_bes_phalanx
ArXiV: https://arxiv.org/abs/1904.04445

#GCPR2019 #Segmentation #CV
3.51K views
Machine learning books and papers
Machine Learning Refined
Foundations, Algorithms, and Applications
JEREMY WATT, REZA BORHANI, AND AGGELOS K. KATSAGGELOS
#book #ML
@Machine_learn
3.16K views
Machine learning books and papers
5_6188486461180870748.pdf
10.9 MB
Machine Learning Refined
Foundations, Algorithms, and Applications
JEREMY WATT, REZA BORHANI, AND AGGELOS K. KATSAGGELOS
#book #ML
@Machine_learn
3.55K views
Machine learning books and papers
Machine Learning for OpenCV
A practical introduction to the world of machine learning and
image processing using #OpenCV and #Python #book #ML
@Machine_learn
3.93K views
Machine learning books and papers
5_6154467025956634927.pdf
27.1 MB
Machine Learning for OpenCV
A practical introduction to the world of machine learning and
image processing using #OpenCV and #Python #book #ML
@Machine_learn
5.06K views
Machine learning books and papers
@Machine_learn
Interpreting Latent Space of GANs for Semantic Face Editing

https://shenyujun.github.io/InterFaceGAN/

code: https://github.com/ShenYujun/InterFaceGAN.git
4.78K views
Machine learning books and papers
@Machine_learn
How to Implement Progressive Growing GAN Models in Keras

https://machinelearningmastery.com/how-to-implement-progressive-growing-gan-models-in-keras/
4.41K viewsRamin Mousa, 
Machine learning books and papers
fundamentals-deep-learning.pdf
15.2 MB
#deeplearning
⬇⬇⬇
@Machine_learn
4.27K viewsArsalan M, edited  
Machine learning books and papers
Machine learning books and papers pinned a file
Machine learning books and papers
@Machine_learn
The HSIC Bottleneck: Deep Learning without Back-Propagation🥺

An alternative to conventional backpropagation, that has a number of distinct advantages.

Link: https://arxiv.org/abs/1908.01580

#backpropagation #DL
arXiv.org
The HSIC Bottleneck: Deep Learning without Back-Propagation
We introduce the HSIC (Hilbert-Schmidt independence criterion) bottleneck for training deep neural networks. The HSIC bottleneck is an alternative to the conventional cross-entropy loss and...
4.3K viewsRamin Mousa, edited  
Machine learning books and papers
Learning_Tenserflow_buliding_deep.pdf
12.6 MB
Learning_Tenserflow_building_deep
#book
@Machine_learn
4.89K viewsparisa, edited  
Machine learning books and papers
Unsupervised learning with python.pdf
33.9 MB
Unsupervised learning with python,2019
#book
@Machine_learn
4.86K viewsparisa, edited  
Machine learning books and papers
@Machine_learn
Rank-consistent Ordinal Regression for Neural Networks

Article: https://arxiv.org/abs/1901.07884

PyTorch: https://github.com/Raschka-research-group/coral-cnn
arXiv.org
Rank consistent ordinal regression for neural networks with...
In many real-world prediction tasks, class labels include information about the relative ordering between labels, which is not captured by commonly-used loss functions such as multi-category...
3.94K viewsRamin Mousa, 
Machine learning books and papers
@Machine_leaen
ai ,machine learning
#code #datasets #paper
• 1146 leaderboards
• 1223 tasks
• 1105 datasets
• 14779 papers with code


https://paperswithcode.com/sota
Paperswithcode
Papers with Code - Browse the State-of-the-Art in Machine Learning
14331 leaderboards • 5880 tasks • 12925 datasets • 168565 papers with code.
4.47K viewsRamin Mousa, 
Machine learning books and papers
@Machine_learn
Memory-Efficient Adaptive Optimization

Source: https://arxiv.org/abs/1901.11150

Code: https://github.com/google-research/google-research/tree/master/sm3
arXiv.org
Memory-Efficient Adaptive Optimization
Adaptive gradient-based optimizers such as Adagrad and Adam are crucial for achieving state-of-the-art performance in machine translation and language modeling. However, these methods maintain...
3.76K viewsRamin Mousa, 
Machine learning books and papers
@Machine_learn
🚀 Introducing TF-GAN: A lightweight GAN library for TensorFlow 2.0

Tensorflow blog: https://medium.com/tensorflow/introducing-tf-gan-a-lightweight-gan-library-for-tensorflow-2-0-36d767e1abae

Code: https://github.com/tensorflow/gan

Free course: https://developers.google.com/machine-learning/gan/

Paper: https://arxiv.org/abs/1805.08318
Medium
Introducing TF-GAN: A lightweight GAN library for TensorFlow 2.0
Posted by Joel Shor, Yoel Drori, Google Research Tel Aviv, Aaron Sarna, David Westbrook, Paige Bailey
4.51K viewsRamin Mousa, 
Machine learning books and papers
@Machine_learn
DeepMind's OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

code: https://github.com/deepmind/open_spiel

article: https://arxiv.org/abs/1908.09453
GitHub
GitHub - google-deepmind/open_spiel: OpenSpiel is a collection of environments and algorithms for research in general reinforcement…
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. - google-deepmind/open_spiel
3.92K viewsRamin Mousa, 
Machine learning books and papers
Deep Learning with Python
The ultimate beginners guide to Learn Deep Learning with Python Step by Step
#book #DL #python
@Machine_learn
3.39K viewsRamin Mousa, 
Machine learning books and papers
4_5994449442294466012.pdf
1.9 MB
Deep Learning with Python
The ultimate beginners guide to Learn Deep Learning with Python Step by Step
#book #DL #python
@Machine_learn
3.81K viewsRamin Mousa, 
2025/07/09 04:35:49
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