Machine learning Tom M
#book
link :https://www.cin.ufpe.br/~cavmj/Machine%20-%20Learning%20-%20Tom%20Mitchell.pdf

@Machine_learn

🚀 TorchSparse: Efficient Point Cloud Inference Engine

Github: https://github.com/mit-han-lab/torchsparse

Paper: https://arxiv.org/abs/2204.10319v1

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

Demo: https://paperswithcode.com/dataset/pipal-perceptual-iqa-dataset

@Machine_leaen

Deep Reinforcement Learning
CS 285, University of California, Berkeley
Harry Zhang December 2019
#book
@Machine_learn

⭐️ Traffic4cast 2022 Competition: from few public vehicle counters to entire city-wide traffic

🖥 Github: https://github.com/iarai/neurips2022-traffic4cast

🗒 Paper: https://arxiv.org/abs/2211.09984v1

➡️ Dataset: https://developer.here.com/sample-data

@Machine_learn

➡️ AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time

🖥 Github: https://github.com/MVIG-SJTU/AlphaPose

📝 Colab: https://colab.research.google.com/drive/1c7xb_7U61HmeJp55xjXs24hf1GUtHmPs?usp=sharing

🗒 Paper: https://arxiv.org/abs/2211.03375v1

➡️ Dataset: https://paperswithcode.com/dataset/hico-det

@Machine_learn

Building Versatile Mobile Apps with Python and REST - 2020
#python #django
@Machine_learn

🚀 Stable Diffusion web UI

UI на основе библиотеки Gradio для Stable Diffusion. Большое количество фич для генерации контента с удобным интерфейсом.

🖥 Github: https://github.com/AUTOMATIC1111/stable-diffusion-webui

⏩ Scripts: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts

⭐️ Features: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features

@Machine_learn

🚀 DiffusionDet: Diffusion Model for Object Detection

DiffusionDet — первая диффузионная модель для обнаружения объектов.

🖥 Github: https://github.com/shoufachen/diffusiondet

➡️ Paper: https://arxiv.org/abs/2211.09788v1

🗒 Getting Started: https://github.com/ShoufaChen/DiffusionDet/blob/main/GETTING_STARTED.md

🖥 Dataset: https://paperswithcode.com/dataset/imagenet

@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

https://bibis.ir/science-books/data/2022/Fundamentals-of-Data-Engineering-by-Joe-Reis-Matt-Housley_bibis.ir.pdf

Fundamentals ofData
Engineering
#book #ML
@Machine_learn

Deep Learning with Keras : : CHEAT SHEET
#Cheat_sheet #keras
@Machine_learn

Data science : : CHEAT SHEET
#Cheat_sheet #DS
@Machine_learn

⏩ PODA: Prompt-driven Zero-shot Domain Adaptation
.

🖥 Github: https://github.com/astra-vision/poda

⏩ Paprer: https://arxiv.org/abs/2212.03241v1

❤️ Pretrainde model: https://drive.google.com/drive/folders/15-NhVItiVbplg_If3HJibokJssu1NoxL?usp=share_link

⭐️ Dataset: https://paperswithcode.com/dataset/cityscapes

@Machine_learn

🔼 IncepFormer: Efficient Inception Transformer with Pyramid Pooling for Semantic Segmentation

🖥 Github: https://github.com/shendu0321/incepformer

✔️ Project: https://github.com/shendu0321/IncepFormer

🗒 Paper: https://arxiv.org/abs/2212.03035v1

➡️ Data: https://paperswithcode.com/dataset/cityscapes

@Machine_learn

•(Multi-Modal Image Fusion)
。(nfrared and visible image fusion)
。 (Medical image fusion)
•(Digital Photography Image Fusion)
。(Multi-exposure image fusion)
。(Multi-focus image fusion)
• (Remote Sensing Image Fusion)
。(Pansharpening)
•(General Image Fusion Framerwork)
#(Survey)
#(Dataset)
#(Evaluation Metric)
#(General evaluation metric
github.com/miao19980215/Image-Fusion


@Machine_learn

✅ pypop7 (Pure-PYthon library of POPulation-based black-box OPtimization)



$ pip install pypop7

🖥 Github: https://github.com/evolutionary-intelligence/pypop

⏩ Paprer: https://arxiv.org/abs/2212.05652v1

⭐️ Derivative-Free Optimization (DFO): https://link.springer.com/article/10.1007/s10208-021-09513-z

@Machine_learn

✔️ ECON: Explicit Clothed humans Obtained from Normals



🖥 Github: https://github.com/YuliangXiu/ECON

⏩ Paprer: https://arxiv.org/abs/2212.07422

📎 Demo: https://github.com/YuliangXiu/ECON#demo

✔️ Instructions: https://github.com/YuliangXiu/ECON#instructions

@Machine_learn