اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
AI and Machine Learning
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Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses
نمایش بیشتر📈 تحلیل کانال تلگرام AI and Machine Learning
کانال AI and Machine Learning (@machine_learning_courses) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 93 668 مشترک است و جایگاه 1 579 را در دسته آموزش و رتبه 3 182 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 93 668 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 11 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 1 097 و در ۲۴ ساعت گذشته برابر 46 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 9.77% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 3.07% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 9 147 بازدید دریافت میکند. در اولین روز معمولاً 2 880 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 17 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند learning, llm, linkedin, linux, udemy تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more!
Buy ads: https://telega.io/c/machine_learning_courses”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 12 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته آموزش تبدیل کردهاند.
93 668
مشترکین
+4624 ساعت
+2967 روز
+1 09730 روز
آرشیو پست ها
93 668
👨💻Top neural network for creating tables
🛠GenSpark — a free neural network that makes tables much better than Excel with one query and without formulas.
🔰 The service generates tables of any size, adds text, graphics, links and pictures, calculates itself and even searches for data on the Internet.
🔗Links:
https://www.genspark.ai/
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What Are LLMs?
📊 Large Language Models are AI systems trained on vast text data to understand and generate human-like language.
🧬 Built on transformer architecture, they predict the next word using patterns in grammar, context, and knowledge.
⚡️ From writing emails to coding and reasoning, they power tools like chatbots and assistants.
🔥 Flaws like bias exist, but they’re reshaping how machines think.
Language is the new code.
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🔅 AI Mastery: LLMs Explained with Math (Transformers, Attention Mechanisms & More)
⏲ 5 hours 📁 34 Lessons
📔 Unlock the secrets behind transformers like GPT and BERT. Learn tokenization, attention mechanisms, positional encoding, and embedding to build and innovate with advanced AI. Excel in the field of machine learning and become a top-tier AI expert.🎙 Taught by: Patrik Szepesi 📤 Download All Courses
93 668
📱Artificial intelligence
📱AI-Powered Software Development: Coding, Testing, and System Design
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🔅 AI-Powered Software Development: Coding, Testing, and System Design
📝 Explore how to effectively leverage generative AI tools across the development lifecycle—from coding and testing to architecture design and agile project management.
🌐 Author: Shaun Wassell
🔰 Level: Intermediate
⏰ Duration: 2h 46m
📋 Topics: AI Software Development, Generative AI Tools, Software Development
🔗 Join Artificial intelligence for more courses
93 668
💻CloudReve
🛠 CloudReve is a self-hosted file management system with multi-cloud support, offering a wide range of features for storing and organizing data.
🔰The system supports various storage backends, upload/download speed limiting, and integration with Aria2.
🔰Users can easily manage files via WebDAV and drag & drop, generate time-limited sharing links, and preview files of various formats online.
🔰CloudReve also allows theme customization and supports multi-user mode, making it a versatile tool for file management.
🔗Links:
https://github.com/cloudreve/Cloudreve?tab=readme-ov-file
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🔎We found a tool for searching PDF files for you
🛠 PDF Search is a document search engine that lets you browse over 18 million PDF documents.
🔰 She will find articles, guides, courses, scientific materials and much more.
⚙️ Some of the service's features:
🔹 Organize your search using smart tags. Click on the tag next to the document preview to find more relevant documents;
🔹 Interactive search. You can find not only a document preview and smart tags, but also a detailed summary and a selection of the most important facts within the document;
🔹 Natural language processing. The service allows you to view rich semantic metadata extracted from thousands of documents;
🔹 Find facts and entities, not just text. The tool goes beyond classic entity identification and returns facts and events hidden in the content.
🔗Links:
https://www.pdfsearch.io/index.php
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In recent times, the popularity of transformer-based LLMs and LLM applications such as AI agents has skyrocketed. Compute is in high demand, while models soar in parameter count—reaching hundreds of billions and trillions of parameters in the largest LLMs.
Luckily, researchers have been moving towards techniques to reduce the compute and VRAM needed to store, train, and run models.
This is where small language models (SLMs) come in. Small language models are neural language models that are much smaller in size (typically billions of parameters or fewer) than today’s massive LLMs (which often have hundreds of billions).
By design, SLMs can run on consumer-grade devices like smartphones, embedded systems, or PCs, offering fast inference and a much lower cost.
Researchers often consider models under about 10 billion parameters to be SLMs, since such models can fit on common hardware with low latency.
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In June of 2025, Nvidia research released a paper detailing the potential of SLMs, titled “Small Language Models are the Future of Agentic AI.”
One of the key takeaways from the paper is that since agents are typically tailored towards solving very specific tasks, a full hundred billion parameter LLM is not required to be proficient at the task.
They show that SLMs are in fact enough for specific agentic applications with examples in specific industries.
SLMs use many state-of-the-art optimization techniques and fine-tuning to decrease the model size and improve efficiency. Some of these techniques allow SLMs to be decently powerful and useful at small sizes. Techniques include quantization, mixture-of-experts (MoE), low rank adaptation (LoRA), pruning, flashattention and more.
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📱Artificial intelligence
📱AI Product Foundations: Planning Strategies for Data Scientists
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🔅 AI Product Foundations: Planning Strategies for Data Scientists
📝 Discover planning strategies, frameworks, and practical skills to build AI products as a data scientist.
🌐 Author: Matthew Blasa
🔰 Level: Intermediate
⏰ Duration: 1h 44m
📋 Topics: Data Science, Artificial Intelligence, Product Strategy
🔗 Join Artificial intelligence for more courses
93 668
🗣SpeechSynthes
🛠SpeechSynthes — free text-to-speech service any length and in any language.
🔰Hundreds of different dialects, the ability to speed and tone settings, voice selection, and convenient export text from files.
🔗 Links:
https://speechsynthesis.online
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13_Neural_Networks_Deep_Learning,_Transfer_Learning_and_TensorFlow.zip443.28 MB
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13_Neural_Networks_Deep_Learning,_Transfer_Learning_and_TensorFlow.zip0.10 KB
