Machine learning books and papers

前往频道在 Telegram

Admin: @Raminmousa1 ID: @Machine_learn link: https://t.me/Machine_learn

显示更多

📈 Telegram 频道 Machine learning books and papers 的分析概览

频道 Machine learning books and papers (@machine_learn) 英语语言赛道中的是活跃参与者。目前社区聚集了 24 369 名订阅者，在教育类别中位列第 8 010，并在伊朗地区排名第 14 011 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 24 369 名订阅者。

根据 15 九月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 -79，过去 24 小时变化为 -3，整体触达仍然可观。

认证状态： 未认证
互动率 (ER)： 平均受众互动率为 7.09%。内容发布后 24 小时内通常能获得 2.18% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 1 729 次浏览，首日通常累积 531 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 4。
主题关注点： 内容集中在 disorder, psy, مقاله, framework, graph 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“Admin: @Raminmousa1 ID: @Machine_learn link: https://t.me/Machine_learn”

凭借高频更新（最新数据采集于 16 九月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为教育类别中的关键影响点。

24 369

订阅者

-324 小时

-357 天

-7930 天

1 729

帖子浏览量

~ 53124 小时

~ 72448 小时

7.09%

参与率

无数据

每日帖子数

Ads index

beta

数据加载中...

相似频道

77.4K

Data Science & Machine Learning

68.3K

Machine Learning with Python

35.0K

Age Of Geeks

2.6K

Best Offers - Courses, Books etc

2.4K

علوم آماری و محاسباتی

更多频道

进出提及

---

吸引订阅者

九月 '26

在2个频道中

八月 '26

+76

在1个频道中

Get PRO

七月 '26

+83

在1个频道中

Get PRO

六月 '26

+44

在1个频道中

Get PRO

五月 '26

+45

在2个频道中

Get PRO

四月 '26

+45

在0个频道中

Get PRO

三月 '26

在0个频道中

Get PRO

二月 '26

+14

在1个频道中

Get PRO

一月 '26

+10

在1个频道中

Get PRO

十二月 '25

+251

在2个频道中

Get PRO

十一月 '25

+522

在11个频道中

Get PRO

十月 '25

+1 065

在2个频道中

Get PRO

九月 '25

+794

在2个频道中

Get PRO

八月 '25

+941

在11个频道中

Get PRO

七月 '25

+835

在3个频道中

Get PRO

六月 '25

+734

在3个频道中

Get PRO

五月 '25

+956

在2个频道中

Get PRO

四月 '25

+1 898

在4个频道中

Get PRO

三月 '25

+658

在7个频道中

Get PRO

二月 '25

+44

在4个频道中

Get PRO

一月 '25

+92

在8个频道中

Get PRO

十二月 '24

+134

在5个频道中

Get PRO

十一月 '24

+394

在13个频道中

Get PRO

十月 '24

+463

在6个频道中

Get PRO

九月 '24

+249

在4个频道中

Get PRO

八月 '24

+387

在3个频道中

Get PRO

七月 '24

+220

在1个频道中

Get PRO

六月 '24

+228

在11个频道中

Get PRO

五月 '24

+422

在2个频道中

Get PRO

四月 '24

+611

在11个频道中

Get PRO

三月 '24

+731

在4个频道中

Get PRO

二月 '24

+1 021

在1个频道中

Get PRO

一月 '24

+1 100

在13个频道中

Get PRO

十二月 '23

+628

在0个频道中

Get PRO

十一月 '23

+409

在11个频道中

Get PRO

十月 '23

+296

在9个频道中

Get PRO

九月 '23

+365

在0个频道中

Get PRO

八月 '23

+467

在0个频道中

Get PRO

七月 '23

+715

在0个频道中

Get PRO

六月 '23

+268

在0个频道中

Get PRO

五月 '23

+107

在0个频道中

Get PRO

四月 '23

+107

在0个频道中

Get PRO

三月 '23

+249

在0个频道中

Get PRO

二月 '23

+110

在0个频道中

Get PRO

一月 '23

+163

在0个频道中

Get PRO

十二月 '22

+118

在0个频道中

Get PRO

十一月 '22

+165

在0个频道中

Get PRO

十月 '22

+101

在0个频道中

Get PRO

九月 '22

+177

在0个频道中

Get PRO

八月 '22

+220

在0个频道中

Get PRO

七月 '22

+229

在0个频道中

Get PRO

六月 '22

+56

在0个频道中

Get PRO

五月 '22

+296

在0个频道中

Get PRO

四月 '22

+411

在0个频道中

Get PRO

三月 '22

+47

在0个频道中

Get PRO

二月 '22

+34

在0个频道中

Get PRO

一月 '22

+44

在0个频道中

Get PRO

十二月 '21

+59

在0个频道中

Get PRO

十一月 '21

+59

在0个频道中

Get PRO

十月 '21

+109

在0个频道中

Get PRO

九月 '21

+454

在0个频道中

Get PRO

八月 '21

+251

在0个频道中

Get PRO

七月 '21

+84

在0个频道中

Get PRO

六月 '21

+183

在0个频道中

Get PRO

五月 '21

+126

在0个频道中

Get PRO

四月 '21

+116

在0个频道中

Get PRO

三月 '21

+101

在0个频道中

Get PRO

二月 '21

+601

在0个频道中

Get PRO

一月 '21

+167

在0个频道中

Get PRO

十二月 '20

+8 834

在0个频道中

日期	订阅者增长	提及	频道
16 九月	0
15 九月	0
14 九月	0
13 九月	+1
12 九月	0
11 九月	0
10 九月	0
09 九月	+1
08 九月	0
07 九月	0
06 九月	0
05 九月	+1
04 九月	+2
03 九月	+1
02 九月	+2
01 九月	+1

频道帖子

با عرض سلام برای یکی از مقالاتمون تحت عنون زیر نیازمند نفر دوم و سوم هستیم. Price: 2 --> 200$ Price 3--> 150$ Title:Skin cancer diagnosis (scd) using efficientnet-wavelet and Optimization algortithms @Raminmousa1

2	🔖Computer Science Fundamentals from MIT We found the textbook Mathematics for Computer Science – covering the mathematics that underlies algorithms and computer science. Logic, graphs, combinatorics, probability, induction, recurrence relations, and discrete structures – all in one place. ⛓️ Link to the textbook https://ocw.mit.edu/courses/6-042j-mathematics-for-computer-science-spring-2015/mit6_042js15_textbook.pdf @Machine_learn	1 744
3	☁️ 24 ساعت تست رایگان سرور ابری ویراک، حالا با اعتبار هدیه بیشتر! اگر قصد راه‌اندازی یا تمدید سرویس‌های ابری خود را دارید، الان بهترین زمان است. ✨ تا پایان مردادماه: 🎁 15% شارژ بیشتر هدیه روی اولین واریزی 🎁 10% شارژ بیشتر هدیه روی تمام واریزی‌های بعدی 🎁 24 ساعت تست رایگان فرقی نمی‌کند اولین بار است که ویراک را انتخاب می‌کنید یا از قبل همراه ما بوده‌اید؛ با هر شارژ، اعتبار بیشتری دریافت می‌کنید و همان زیرساخت قدرتمند را با هزینه کمتر در اختیار خواهید داشت. برای دریافت کد تست رایگان کلمه «تست» رو به آیدی زیر ارسال کنید. https://t.me/cloud_virak 👇 پس از دریافت کد تست رایگان وارد پنل VirakCloud شوید ، کد تخفیف خود را وارد نمایید و ابرک خود را بسازید: 🔗 https://B2n.ir/qy4432 ☎️ 02191555530	435
4	Matrix Calculus for Machine Learning and Beyond! — a free ebook from MIT. This is the 2025 MIT textbook by Alan Edelman, Steven G. Johnson, and Paige Bright. The book directly connects matrix calculus to modern machine learning. Inside: * Derivatives of matrices and vectors * Jacobian and Hessian * Matrix decompositions * Optimization * Differentiation in reverse mode * Backpropagation of error * Automatic differentiation * Derivatives through ODEs * Problems focused on machine learning This is a comprehensive mathematical bridge between linear algebra, calculus, optimization, backpropagation, and machine learning. Free ebook: https://geni.us/Matrix-Calculus-Book @Machine_learn	2 241
5	🔖 ML algorithms in visualizations A useful repository that helps you understand how machine learning algorithms work – through interactive diagrams and step-by-step explanations. You can run it in your browser or locally using Docker. ⛓ Link to GitHub https://github.com/gavinkhung/machine-learning-visualized @Machine_learn	2 547
6	"The Mathematics of Bitcoin" is a concise work that analyzes Bitcoin from a mathematical perspective. 📊 It utilizes probability theory, stochastic processes, martingales, combinatorics, and special functions to explore the mechanisms of the Bitcoin protocol. 🧮 In particular, the authors examine the probability of double-spending, the profitability of mining, block generation, miner strategies, and the resilience of the protocol. ⛏️ If you want to delve deeper, I also recommend "Bitcoin and Cryptocurrency Technologies" from Princeton University. This is a much broader introduction to cryptographic hash functions, digital signatures, consensus, Proof of Work, mining, transactions, anonymity, security, and the incentive system in cryptocurrencies. 🎓 The Mathematics of Bitcoin: https://arxiv.org/pdf/2003.00001 Bitcoin and Cryptocurrency Technologies: https://d28rh4a8wq0iu5.cloudfront.net/bitcointech/readings/princeton_bitcoin_book.pdf @Machine_learn	3 006
7	🔥 8 skills = 8 free certifications >>> AI (Microsoft) - https://learn.microsoft.com/en-us/training/paths/get-started-artificial-intelligence/ Deep learning (NVIDIA) - https://learn.nvidia.com/en-us/training/self-paced-courses Data science (IBM) - https://skillsbuild.org/students/course-catalog/data-science Data Analyst (Microsoft) - https://learn.microsoft.com/en-us/training/paths/data-analytics-microsoft/ Python (Microsoft) - https://learn.microsoft.com/en-us/shows/intro-to-python-development/ SQL (Infosys) - https://www.coursejoiner.com/freeonlinecourses/infosys-free-certification-course-9/ Java (Infosys) - https://www.coursejoiner.com/uncategorized/infosys-launched-free-java-certification-course/ Cloud computing (AWS) - https://explore.skillbuilder.aws/learn/course/134/aws-cloud-practitioner-essentials @Machine_learn	2 633
8	اخرین زمان سابمیت این مقاله امشب...! @Raminmousa1	2 353
9	با عرض سلام در مقاله زیر جهت سابمیت نیاز به نفر دوم داریم Title: FFChurn: Fusion Former for Customer Churn Classification Based on Transformer, FEDformer, and Informer Abstract: Customer churn prediction is a key issue in customer relationship management that directly impacts organizational profitability and has created challenges for researchers and organizations. Machine learning (ML), Ensemble Learning (EL), and Deep Learning (DL) models have achieved comparable results on this problem. In this study, Fusion Former was introduced, integrating the FEDformer, Informer, and Transformer architectures to simultaneously extract local features and long-term dependencies. The pipeline for this model includes denoising with a wavelet transform, Min-Max normalization, and hybrid adaptive feature selection based on mutual information (MI), recursive feature elimination (RFE), and the Boruta algorithm. Four different versions of the model, including binary and ternary object fusion, were evaluated on two datasets. The results showed that the Fusion Former (FED+INF+Transformer) model, with F1 scores of 0.9876 on the Dataset 1 and 0.8887 on the Dataset 2, outperformed classical machine learning models, multilayer neural networks, and other binary combinations. Also, the sensitivity analysis of hyperparameters, which included changes in the cost function, batch size, and dropout size, methods for dealing with data imbalance, which included Smote, TMG-GAN, Ib-gan, T-SMOTE approaches, and the effect of feature selection, which included four methods: MI, RFE, Boruta, and Adaptive FS (Boruta+MI+RFE), confirmed the superiority and relative stability of the proposed model. Price:250$ @Raminmousa1 @Machine_learn	2 561
10	report2 (1).pdf	2 366
11	🔖 Learning Data Science through interactive examples One of the most useful repositories for those who want to better understand machine learning. It transforms complex concepts into visual experiments: you can study models, change parameters, and immediately see the results. ⛓ Link to GitHub https://github.com/GeostatsGuy/DataScienceInteractivePython @Machine_learn	2 536
12	Attention Heatmap vs Token Pruning 🔍✂️ 🔗 More: https://www.overshoot.ai/blogs/an-introduction-to-token-pruning-for-vlms #AI #MachineLearning #TokenPruning #DeepLearning #TechNews #VLM @Machine_learn	2 078
13	با عرض سلام سه موضوع زیر جهت نگارش مقالات مدنظر داریم. که در هر سه مقاله به دو جایگاه نیاز داریم. مقالات کاملا مشارکتی هست و علاوه بر تقبل هزینه کار نیز باید انجام بشه. 1: Survey on knowledge graph and large language models _ auth2: 300$ _auth3:200$ 2: Survey on challenges of large language models _ auth2: 300$ _auth3:200$ 3: New learning model for skin cancer detection _ auth2: 300$ _auth3:200$ جهت مشارکت میتونین با ایدی بنده در ارتباط باشین. زمان شروع هر مقاله یک هفته بعد از تشکیل تیم. @Raminmousa1 @Machine_learn	2 255
14	🔖 One of the most useful books on Agentic AI This is not just a textbook, but a comprehensive overview of modern LLMs, model training, RL, inference, quality assessment, and building AI agents. It's an excellent option to get a holistic picture and understand which topics deserve deeper study. ⛓️ Link to the book https://arxiv.org/abs/2606.24937 @Machine_learn	1 798
15	Maths, CS & AI Compendium: A free textbook for aspiring AI/ML engineers 🚀 A large open-source compendium on mathematics, computer science, and AI has gone viral on GitHub. The project already has around 6.3K stars. 📚 The author positions it as a "non-traditional textbook" for practitioners: less dry notation, more intuition, connections between topics, and real-world context. 📖 It contains 20 chapters: * Vectors, matrices, calculus * Statistics and probability * Machine learning and deep learning * NLP, computer vision, audio/speech * Multimodal learning and autonomous systems * GNN, OS, algorithms * Production engineering, GPU/SIMD * AI inference, ML systems design, and applied AI 💡 This is a great resource for those who want to not just "learn ML," but to build a solid foundation: mathematics → CS → ML systems → modern AI. 🔗 GitHub: https://github.com/HenryNdubuaku/maths-cs-ai-compendium @Machine_learn	1 765
16	10 GitHub repositories that are worth checking out for an AI engineer 🤖 1. Hands-On AI Engineering 🛠️ A collection of AI applications and agent systems with practical use cases of LLM. 👉 https://github.com/Sumanth077/Hands-On-AI-Engineering 2. Hands-On Large Language Models 📘 👉 https://github.com/HandsOnLLM/Hands-On-Large-Language-Models 3. AI Agents for Beginners 🎓 👉 https://github.com/microsoft/ai-agents-for-beginners 4. GenAI Agents 🤖 👉 https://github.com/NirDiamant/GenAI_Agents 5. Made With ML 🚀 👉 https://github.com/GokuMohandas/Made-With-ML 6. Learn Harness Engineering ⚙️ 👉 https://github.com/walkinglabs/learn-harness-engineering 7. AutoResearch 🔬 👉 https://github.com/karpathy/autoresearch 8. Designing Machine Learning Systems 📚 👉 https://github.com/chiphuyen/dmls-book 9. Awesome LLM Inference ⚡ 👉 https://github.com/xlite-dev/Awesome-LLM-Inference 10. LLM Course 🗺️ 👉 https://github.com/mlabonne/llm-course	2 274
17	🔖 Comprehensive Practical Course on Reinforcement Learning We've found a repository that will help you learn Reinforcement Learning, from basic concepts to advanced algorithms. The author supports the theory with practical examples using TensorFlow, making the material ideal for self-study. ⛓️ Link to GitHub https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow @Machine_learn	1 940
18	+1 با عرض سلام مقاله زیر جهت واگذاری اسامی در نظر گرفته شده است Title: A Multi-Task Framework Unifying Classification and Regression forMicrogrid Power (kWh) Forecasting: Modified FEDformer Journal: IEEE transaction on soft computing Price: 2: 500$ 3: 350$ @Raminmousa1	387
19	Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models Read @Machine_learn	2 630
20	🔥 Awesome open-source project to learn more about Transformer Models! 🤖✨ We found this interactive website that shows you visually how transformer models work. 🌐📊 Transformer Explainer: https://poloclub.github.io/transformer-explainer/ @Machine_learn	2 235

查看所有帖子