R and Python for oceanographers

⬇️ Book

@Machine_learn

Self-Supervised Learning with Swin Transformers

Github: https://github.com/SwinTransformer/Transformer-SSL

Paper: https://arxiv.org/abs/2105.04553v2

@Machine_learn

SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full-Image Warping

Paper:
https://arxiv.org/pdf/2105.07014.pdf

Video:
https://www.youtube.com/watch?v=W7NCbfZp6QE

Code:
https://github.com/google-research/google-research/tree/master/smurf

@Machine_learn

GIRAFFE: A Closer Look at the Code for CVPR 2021’s Best Paper

[Paper] http://www.cvlibs.net/publications/Niemeyer2021CVPR.pdf

[Source] https://github.com/autonomousvision/giraffe

[Blog] https://autonomousvision.github.io/giraffe/

[Interactive slides] https://m-niemeyer.github.io/slides/#/4

[Collected] https://m-niemeyer.github.io/project-pages/giraffe/index.html

@Machine_learn

Jason Brownlee
Master Machine Learning Algorithms Discover How They Work and Implement Them From Scratch
#Ml #book
@Machine_learn

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