🔍 Contrastive Sensor Fusion

Github: https://github.com/descarteslabs/contrastive_sensor_fusion

Paper: https://arxiv.org/abs/2108.05094v1

@Machine_learn

📹 Internal Video Inpainting by Implicit Long-range Propagation

Github: https://github.com/Tengfei-Wang/Implicit-Internal-Video-Inpainting

Paper: https://arxiv.org/abs/2108.01912v1

4k Data: https://github.com/Tengfei-Wang/Annotated-4K-Videos

Dataset: https://paperswithcode.com/dataset/videoremoval4k

@Machine_learn

Quantum Machine Learning with Python - 2021
#Quantum #book #2021
@Machine_learn

Deep Learning and Physics
#book #2021 #DL #Physics
@Machine_learn

PyTorch Pocket Reference (2021)
#book #2021 #PyTorch
@Machine_learn

Thai Natural Language
Processing
Word Segmentation, Semantic Analysis,
and Application #NLP #Book #2021
@Machine_learn

Formalising Natural
Languages: Applications
to Natural Language
Processing and Digital
Humanities #NLP #Book #2021

@Machine_learn

Hands-on Question
Answering Systems
with BERT
Applications in Neural
Networks and Natural
Language Processing #NLP #BERT #book #2021

@Machine_learn

Synthetic Data for Deep
Learning #DL #book #2021

@Machine_learn

Image Processing
and Capsule Networks
ICIPCN 2020 #CapsuleNet #DL #image #book #2020

@Machine_learn

Beginning Robotics
with Raspberry Pi
and Arduino
Using Python and OpenCV
Second Edition #OpenCv #book #2021

@Machine_learn

Smart Computing
Techniques and Applications
Proceedings of the Fourth International
Conference on Smart Computing
and Informatics, Volume 1 #book #2021

@Machine_learn

🔍 TOOD: Task-aligned One-stage Object Detection

Github: https://github.com/fcjian/TOOD

Paper: https://arxiv.org/abs/2108.07755v2

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

@Machine_learn

🔗 A Unified Objective for Novel Class Discovery

Github: https://github.com/DonkeyShot21/UNO

Paper: https://arxiv.org/abs/2108.08536v2

Dataset: https://paperswithcode.com/dataset/cifar-100

@Machine_learn

💡 X-modaler: A Versatile and High-performance Codebase for Cross-modal Analytics

Github: https://github.com/yehli/xmodaler

Paper: https://arxiv.org/abs/2108.08217v1

Project: https://xmodaler.readthedocs.io/en/latest/

@Machine_learn

🧍‍♂ D3D-HOI: Dynamic 3D Human-Object Interactions from Videos

Github: https://github.com/facebookresearch/d3d-hoi

Paper: https://arxiv.org/abs/2108.08420v1

Dataset: https://dl.fbaipublicfiles.com/d3d-hoi/d3dhoi_video_data.zip

@Machine_learn

🕸 Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study

Github: https://github.com/VITA-Group/Deep_GCN_Benchmarking

Paper: https://arxiv.org/abs/2108.10521v1

@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

Advanced Machine Learning with Python
#python #book #2021
@Machine_learn