Telegram Web Link
Mathematical theory of deep learning

📚 Book

@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
Deep Learning and Computational Physics - Lecture Notes, University of South California

📓 book

@Machine_learn
Financial Machine Learning

📓 book

@Machine_learn
Generalizable and Animatable Gaussian Head Avatar

🖥 Github: https://github.com/xg-chu/gagavatar

📕 Paper: https://arxiv.org/abs/2410.07971v1

@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
Artificial Intelligence A Modern Approach

📚 Book

@Machine_learn
📃Fake news detection: A survey of graph neural network methods

📎 Study paper


@Machine_learn
UC Berkeley's "Machine Learning" lecture notes

📓 Book

@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
Probability and Statistics The Science of Uncertainty

📖 book

@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
با عرض سلام خيلي از دوستان در رابطه با طراحي صفر تا صد پروژه هاي ديپ از بنده سوال پرسيدن داخل پك زير ٣٦ پروژه رو با جزئيات شرح دادم:

1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
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
دوستاني كه نياز به اين پروژه ها دارن ميتونن با بنده در ارتباط باشن.
@Raminmousa
@Machine_learn
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts

💻 Github: https://github.com/freedomintelligence/apollomoe

🔖 Paper: https://arxiv.org/abs/2410.10626v1

🤗 Dataset: https://paperswithcode.com/dataset/mmlu

@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
Neural Networks and Deep Learning

📓 book

@Machine_learn
Thesis2 2.pdf
5.5 MB
Thesis: Yolo object detection

این پروژه سال ۲۰۲۰ با یکی از دوستان انجام دادیم که هدف تشخیص وزن پل با استفاده از Yolo بود. جزئیات مدل یولو رو داخل این بررسی کردیم . برای دوستانی که می خوان بیشتر این مدل رو بررسی کنن می تونه مفید باشه.
@Machine_learn
📃Network Modeling and Control of Dynamic Disease Pathways, Review and Perspectives


📎 Study the paper

@Machine_learn
📑 Nine quick tips for open meta-analyses


📎 Study the paper

@Machine_learn
Algebraic topology for physicists

📓 Book

@Machine_learn
✔️ LVD-2M: A Long-take Video Dataset with Temporally Dense Captions

New pipeline for selecting high-quality long-take videos and generating temporally dense captions.

Dataset with four key features essential for training long video generation models: (1) long videos covering at least 10 seconds, (2) long-take videos without cuts, (3) large motion and diverse contents, and (4) temporally dense captions.

🖥 Github: https://github.com/silentview/lvd-2m

📕 Paper: https://arxiv.org/abs/2410.10816v1

🖥 Dataset: https://paperswithcode.com/dataset/howto100m

🔸@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
Forwarded from Github LLMs
🔥 NVIDIA silently release a Llama 3.1 70B fine-tune that outperforms
GPT-4o and Claude Sonnet 3.5


Llama 3.1 Nemotron 70B Instruct a further RLHFed model on
huggingface


https://huggingface.co/collections/nvidia/llama-31-nemotron-70b-670e93cd366feea16abc13d8
https://www.tg-me.com/deep_learning_proj
Please open Telegram to view this post
VIEW IN TELEGRAM
Prompt Engineering Techniques: Comprehensive Repository for Development and Implementation 🖋️

📓 Github

@Machine_learn
2024/11/16 11:42:24
Back to Top
HTML Embed Code: