EL-Attention: Memory Efficient Lossless Attention for Generation

Github: https://github.com/microsoft/fastseq

Paper: https://arxiv.org/abs/2105.04779v1

@Machine_learn

Deep Learning Dataset For Passage and Document Retrieval

Github: https://github.com/grill-lab/DL-Hard

Paper: https://arxiv.org/abs/2105.07975v1

@Machine_learn

Cartoon-StyleGan2 🙃 : Fine-tuning StyleGAN2 for Cartoon Face Generation

Github: https://github.com/happy-jihye/Cartoon-StyleGan2

Paper: https://arxiv.org/abs/2106.12445

Colab: https://colab.research.google.com/github/happy-jihye/Cartoon-StyleGan2/blob/main/Cartoon_StyleGAN2.ipynb

@Machine_learn

Neural Networks and Introduction to Deep Learning
#RNN #DL
@Machine_learn

🌠 Deepmind's Generally capable agents emerge from open-ended play

Blog : https://deepmind.com/blog/article/generally-capable-agents-emerge-from-open-ended-play

Paper: https://deepmind.com/research/publications/open-ended-learning-leads-to-generally-capable-agents

DeepMind Research: https://github.com/deepmind/deepmind-research

Video: https://www.youtube.com/watch?v=lTmL7jwFfdw&ab_channel=DeepMind

@Machine_learn

A Dataset for Studying Gender Bias in Translation


http://ai.googleblog.com/2021/06/a-dataset-for-studying-gender-bias-in.html

@Machine_learn

Deep Learning based Vehicle Detection in Aerial Imagery
Sommer, Lars Wilko #2021 #book #DL @Mchine_learn

Deep Learning
with Python
Learn Best Practices of
Deep Learning Models
with PyTorch Ketkar, Nikhil ; Moolayil, Jojo #2021 #DL #Book #PyTorch @Machine_learn

با عرض سلام ما پكيج ٣٦ پروژه عملي با يادگيري عميق همراه با داكيومنت فارسي را براي دوستاني كه مي خواهند در اين حوزه به صورت عملي كار كنند تهيه كرديم سرفصل هاي اين پكيج به ترتيب زير مي باشند:


1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
--02_Creating_and_Using_Tensors
--03_Implementing_Activation_Functions
-02_TensorFlow_Way
--01_Operations_as_a_Computational_Graph
--02_Implementing_Loss_Functions
--03_Implementing_Back_Propagation
--04_Working_with_Batch_and_Stochastic_Training
--05_Evaluating_Models
-03_Linear_Regression
--linear regression
--Logistic Regression
-04_Neural_Networks
--01_Introduction
--02_Single_Hidden_Layer_Network
--03_Using_Multiple_Layers
-05_Convolutional_Neural_Networks
--Convolution Neural Networks
--Convolutional Neural Networks Tensorflow
--TFRecord For Deep learning Models
-06_Recurrent_Neural_Networks
--Recurrent Neural Networks (RNN)
2-Classification apparel
-Classification apparel double capsule
-Classification apparel double cnn
3-ALZHEIMERS USING CNN(ResNet)
4-Fake News (Covid-19 dataset)
-Multi-channel
-3DCNN model
-Base line+ Char CNN
-Fake News Covid CapsuleNet
5-3DCNN Fake News
6-recommender systems
-GRU+LSTM MovieLens
7-Multi-Domain Sentiment Analysis
-Dranziera CapsuleNet
-Dranziera CNN Multi-channel
-Dranziera LSTM
8-Persian Multi-Domain SA
-Bi-GRU Capsule Net
-Multi-CNN
9-Recommendation system
-Factorization Recommender, Ranking Factorization Recommender, Item Similarity Recommender (turicreate)
-SVD, SVD++, NMF, Slope One, k-NN, Centered k-NN, k-NN Baseline, Co-Clustering(surprise)
10-NihX-Ray
-optimized CNN on FullDataset Nih-Xray
-MobileNet
-Transfer learning
-Capsule Network on FullDataset Nih-Xray
هزينه اين پكيج ٥٠٠هزار مي باشد و صرفا هزينه تهيه ديتاست هاست.
جهت خريد مي توانيد با ايدي بنده در ارتباط باشيد
@Raminmousa

🥑 DALL·E Mini

Generate images from a text prompt

Demo: https://huggingface.co/spaces/flax-community/dalle-mini

Github: https://github.com/borisdayma/dalle-mini

Paper: https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini--Vmlldzo4NjIxODA

@Machine_learn

Introduction
to Deep
Learning
From Logical Calculus to Artificial
Intelligence #book #DL #2018 @Machine_learn

Machine Learning
für Zeitreihen
Einstieg in Regressions-, ARIMAund
Deep-Learning-Verfahren
mit Python #Book #DL #2021 @Machine_learn

Computational
Science – ICCS 2021 #2021 #book #DL #Cs @Machine_learn

Tokyo Olympics Alternative medals table

Article on how teams performed with the respect to behavior expected by regression model.

Link: https://ig.ft.com/tokyo-olympics-alternative-medal-table/

@Machine_learn

Graph Convolutional Neural Networks to Analyze Complex Carbohydrates

A blog post by Daniel Bojar about an application of GNN to analyzing glycan sequences and their proposed GNN architecture called SweetNet. There are other coverages of this work (here and here). The paper is here and the code is here.

@Machine_learn