This is definitely between new and experienced programmer :D

https://www.tg-me.com/Machine_learn

Real-Time IoT Imaging with Deep Neural Networks - 2020
#Neural_Networks #english @Machine_learn

Grounding Visual Representations with Texts for Domain Generalization

Github: https://github.com/mswzeus/gvrt

Paper: https://arxiv.org/abs/2207.10285v1

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

@Machine_learn

🏎 Instance Shadow Detection with A Single-Stage Detector

Deep framework, and an evaluation metric to approach this new task.

Github: https://github.com/stevewongv/InstanceShadowDetection

Instance Shadow Detection: https://github.com/stevewongv/SSIS

Video: https://www.youtube.com/watch?v=p0b_2SsFypw

Colab: https://colab.research.google.com/drive/1y9UpS5uA1YuoMyvYVzcKL4ltA_FDu_x0?usp=sharing

Paper: https://arxiv.org/abs/2207.04614v1

Datasets: https://paperswithcode.com/dataset/soba

@Machine_learn

Python code for Artificial Intelligence: Foundations of Computational Agents
David L. Poole and Alan K. Mackworth
#book #2022
@Machine_learn

Computer Vision and Augmented Reality in iOS
OpenCV and ARKit Applications
Ahmed Fathi Bekhit
#book #2022
@Machine_learn

با عرض سلام دو پکیچ یادگیری ماشین و یادگیری عمیق را برای دوستانی که می خواهند تا فرداشب با تخفیف ۵۰٪ مجدد قرار دادیم این تخفیف اخرین سری از تخفیف های این دو پکیچ می باشد
1: introduction to machine learning
2: Regression (linear and non-linear)
3: Tensorflow introduction
4: Tensorflow computaion graph
5: Tensorflow optimizer and loss function
6: Tensorflow linear and non linear regression
7: logistic regression
8: Tensorflow regression
___________
9: introduction to traditional machine learning
*10: knn and desicion tree
*11: desicion tree and Naive bayes
*12: desicion tree, knn, Naive bayes implementation
*13: k-means
*14: Guassion Mixture Model(GMM)
*15: implementation K-means and GMM
_________
16: introduction to Artificial Neural Network
17: Multi-level Neural Network
18: Introduction to Convolution Neural Network
19: Tensorflow Multi-level Neural Network
20:Tensorflow CNN
21:CNN image clasaification
22: Cnn text clasaification
23: Recurrent Neural Network(RNN)

جهت تهیه می تونین به ایدی بنده مراجعه کنین

@Raminmousa

Class-incremental Novel Class Discovery

Github: https://github.com/oatmealliu/class-incd

Paper: https://arxiv.org/abs/2207.08605v1

Dataset: https://paperswithcode.com/dataset/tiny-imagenet

@Machine_learn

🎯 Object-Compositional Neural Implicit Surfaces

Github: https://github.com/qianyiwu/objsdf

Paper: https://arxiv.org/abs/2207.09686v1

Project: https://qianyiwu.github.io/objectsdf/

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

@Machine_learn

Distance Learner: Incorporating Manifold Prior to Model Training

Github: https://github.com/microsoft/distance-learner

Paper: https://arxiv.org/abs/2207.06888v1

Project: https://fast-vid2vid.github.io/

@Machine_learn

Deep Learning for the Life Sciences
#book
#2019
@Machine_learn

Data visualization with python
#book
@Machine_learn

با عرض سلام دو پکیچ یادگیری ماشین و یادگیری عمیق را برای دوستانی که می خواهند تا فرداشب با تخفیف ۵۰٪ مجدد قرار دادیم این تخفیف اخرین سری از تخفیف های این دو پکیچ می باشد
1: introduction to machine learning
2: Regression (linear and non-linear)
3: Tensorflow introduction
4: Tensorflow computaion graph
5: Tensorflow optimizer and loss function
6: Tensorflow linear and non linear regression
7: logistic regression
8: Tensorflow regression
___________
9: introduction to traditional machine learning
*10: knn and desicion tree
*11: desicion tree and Naive bayes
*12: desicion tree, knn, Naive bayes implementation
*13: k-means
*14: Guassion Mixture Model(GMM)
*15: implementation K-means and GMM
_________
16: introduction to Artificial Neural Network
17: Multi-level Neural Network
18: Introduction to Convolution Neural Network
19: Tensorflow Multi-level Neural Network
20:Tensorflow CNN
21:CNN image clasaification
22: Cnn text clasaification
23: Recurrent Neural Network(RNN)

جهت تهیه می تونین به ایدی بنده مراجعه کنین

@Raminmousa

Language Modelling with Pixels

PIXEL is a language model that operates on text rendered as images, fully removing the need for a fixed vocabulary.

Github: https://github.com/xplip/pixel

Paper: https://arxiv.org/abs/2207.06991v1

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

Pretrained: https://huggingface.co/Team-PIXEL/pixel-base

@Machine_learn

سلام با توجه به مساله فیلترینگ دوستانی که نیاز به مشاوره و یا سوالی داشتند می تونن به شماره بنده پیام بدن یا تماس بگیرن 00989333900804

🔲 TensorStore

Novel open-source C++ / #Python library for storage/manipulation of high-dim data

⚙️ Github
🗒 Tutorial
📌 Google AI
🦾 Docs

@Machine_learn

🎓 YATO: Yet Another deep learning based Text analysis Open toolkit

pip install ylab-yato

⚙️ Github
📋 Paper
📌 Dataset

@Machine_learn