PlenOctrees For Real-time Rendering of Neural Radiance Fields

And yet another speed-up of NERF. Exactly the same idea as in FastNeRF and NEX (predict spherical harmonics coefficients k) - incredible! It's the first time I see so many concurrent papers sharig the same idea. But this one has code at least, which makes it the best!

📝 Paper arxiv.org/abs/2103.14024
🌐Project page alexyu.net/plenoctrees/
🛠Code github.com/sxyu/volrend


@Machine_learn

Data Analysis with python
#book #python

@Machine_learn

​​EfficientNetV2: Smaller Models and Faster Training

A new paper from Google Brain with a new SOTA architecture called EfficientNetV2. The authors develop a new family of CNN models that are optimized both for accuracy and training speed. The main improvements are:

- an improved training-aware neural architecture search with new building blocks and ideas to jointly optimize training speed and parameter efficiency;
- a new approach to progressive learning that adjusts regularization along with the image size;

As a result, the new approach can reach SOTA results while training faster (up to 11x) and smaller (up to 6.8x).

Paper: https://arxiv.org/abs/2104.00298

Code will be available here:
https://github.com/google/automl/efficientnetv2

A detailed unofficial overview of the paper: https://andlukyane.com/blog/paper-review-effnetv2

@Machine_learn

500 + 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗟𝗶𝘀𝘁 𝘄𝗶𝘁𝗵 𝗰𝗼𝗱𝗲

500 AI Machine learning Deep learning Computer vision NLP Projects with code

This list is continuously updated. - You can take pull request and contribute.

https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

@Machine_learn

Complete Python Bootcamp 2021.pdf
@Machine_learn

Fashion Meets Computer Vision: A Survey @Machine_learn

🧠 Lite-HRNet: A Lightweight High-Resolution Network

Github: https://github.com/HRNet/Lite-HRNet

Paper: https://arxiv.org/abs/2104.06403

@Machine_learn

Simple multi-dataset detection

Github: https://github.com/xingyizhou/UniDet

Paper: https://arxiv.org/abs/2102.13086v1

@Machine_learn

Monster Mash: A Sketch-Based Tool for Casual 3D Modeling and Animation


http://ai.googleblog.com/2021/04/monster-mash-sketch-based-tool-for.html

@Machine_learn

Flexible, Scalable, Differentiable Simulation of Recommender Systems with RecSim NG


http://ai.googleblog.com/2021/04/flexible-scalable-differentiable.html

@Machine_learn

How Machine Learning is Changing e-Government @Machine_learn

Google at ICLR 2021


http://ai.googleblog.com/2021/05/google-at-iclr-2021.html

@Machine_learn

tf.keras.Model

https://www.tensorflow.org/api_docs/python/tf/keras/Model

Code: https://github.com/tensorflow/tensorflow/blob/v2.4.1/tensorflow/python/keras/engine/training.py#L138-L2675

@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

A Survey of Data Augmentation Approaches for NLP

Data Augmentation has becoming more and more popular and important task in NLP. On the contrary to Computer Vision where all methods now are well-known and already pre-implemented in libraries, in NLP the situation is not so consistent.

So, there has been published a nice paper that accumulated all known due today techniques, models and applications of data augmentation in texts:
https://arxiv.org/abs/2105.03075

In the appendix you can find the list of open-source that may be useful for your task.
@Machine_learn