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Machine learning books and papers
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Admin: @Raminmousa ID: @Machine_learn link: https://t.me/Machine_learn
Ko'proq ko'rsatish📈 Telegram kanali Machine learning books and papers analitikasi
Machine learning books and papers (@machine_learn) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 24 502 obunachidan iborat bo'lib, Taʼlim toifasida 8 036-o'rinni va Eron mintaqasida 13 785-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
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- Tematik yo‘nalishlar: Kontent disorder, psy, مقاله, framework, graph kabi asosiy mavzularga jamlangan.
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“Admin: @Raminmousa
ID: @Machine_learn
link: https://t.me/Machine_learn”
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24 502
Obunachilar
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-207 kunlar
-12730 kunlar
Postlar arxiv
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics
Github: https://github.com/mims-harvard/TDC
Paper: https://arxiv.org/abs/2102.09548
Datasets: https://tdcommons.ai/
@Machine_learn
Python for data science cheatsheet
#python #chearsheet
@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 ٥٠٠هزارمیباشد(صرفا هزينه تهيه ديتاست هاست).
جهت خريد مي توانيد با ايدي بنده در ارتباط باشيد
@Raminmousa
Introducing Model Search: An Open Source Platform for Finding Optimal ML Models
http://ai.googleblog.com/2021/02/introducing-model-search-open-source.html
@Machine_learn
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software
Github: https://github.com/EdisonLeeeee/GraphGallery
Paper: https://arxiv.org/abs/2102.07933v1
@Machine_learn
🔸لیستی از برترین کانالهای آموزشی در زمینه های هوشمصنوعی, پایتون و یادگیری ماشین
❯ هوش مصنوعی:
1️⃣ @Ai_Tv
2⃣ @AI_PYTHON
3⃣ @cvision
4⃣ @HomeAI
❯ یادگیری ماشین و یادگیری عمیق :
1️⃣ @Machine_learn
❯ علم داده:
1⃣ @dataanalysis
2⃣ @python4finance
3⃣ @mr_ie
❯ آموزش پایتون :
1⃣ @pythony
2⃣ @pythonchallenge
3⃣ @SQL_Server
4⃣ @Koolac_Org
5⃣ @Raspberry_Python
6⃣ @Programming4all_0to100
TI-Capsule: Capsule Network for Stock Exchange Prediction
#Paper
@Raminmousa
@Machine_learn
🧪 Alchemy: A structured task distribution for meta-reinforcement learning
Deepmind: https://deepmind.com/research/publications/alchemy
Github: https://github.com/deepmind/dm_alchemy
Paper: https://arxiv.org/abs/2102.02926
@Machine_learn
How to Speed up Scikit-Learn Model Training
https://www.kdnuggets.com/2021/02/speed-up-scikit-learn-model-training.html
@Machine_learn
📌کانالی مناسب برای علاقه مندان هوش مصنوعی، یادگیری ماشین، زبان برنامه نویسی پایتون و آموزش های رایگان
📝 این کانال توسط فارغ التحصیلان هوش مصنوعی دانشگاه صنعتی امیرکبیر ایجاد شده و جدیدترین اخبار حوزه هوش مصنوعی را اطلاع رسانی خواهد کرد.
https://t.me/joinchat/AAAAADweGusEx9ZAwC-N0g
📍متخصصین و اساتید زیادی در این کانال عضو هستند.
📖 مجله هوش مصنوعی
➖➖➖➖➖
🆔 : @HomeAI
Neural-Backed Decision Trees
Demo: https://research.alvinwan.com/neural-backed-decision-trees/
Github: https://github.com/alvinwan/neural-backed-decision-trees
Paper: https://arxiv.org/abs/2004.00221
Code: https://colab.research.google.com/github/alvinwan/neural-backed-decision-trees/blob/master/examples/load_pretrained_nbdts.ipynb
Dataset: https://pytorch.org/docs/stable/torchvision/datasets.html
@Machine_learn
Building Image Segmentation Faster Using Jupyter Notebooks from NGC
https://developer.nvidia.com/blog/building-image-segmentation-faster-using-jupyter-notebooks-from-ngc/
@Machine_learn
ML Algorithms Cheatsheet (python and R)
#code #python #R
@Machine_learn
Super VIP Cheatsheet: Machine Learning
Afshine Amidi and Shervine Amidi
#ML
@Machine_learn
Quantum Computing and Blockchain in Business (2020)
#book #2020 #Blockchain
@Machine_learn
Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning
http://ai.googleblog.com/2021/02/evaluating-design-trade-offs-in-visual.html
@Machine_learn
TracIn — A Simple Method to Estimate Training Data Influence
http://ai.googleblog.com/2021/02/tracin-simple-method-to-estimate.html
@Machine_learn
