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Artificial Intelligence

Artificial Intelligence

Kanalga Telegram’da o‘tish

🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data

Ko'proq ko'rsatish

📈 Telegram kanali Artificial Intelligence analitikasi

Artificial Intelligence (@machinelearning_deeplearning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 53 216 obunachidan iborat bo'lib, Taʼlim toifasida 3 245-o'rinni va Hindiston mintaqasida 7 023-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 53 216 obunachiga ega bo‘ldi.

11 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 1 051 ga, so‘nggi 24 soatda esa 27 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 6.06% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.66% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 3 222 marta ko‘riladi; birinchi sutkada odatda 884 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 10 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent learning, classification, layer, pattern, chatbot kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data

Yuqori yangilanish chastotasi (oxirgi ma’lumot 12 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

53 216
Obunachilar
+2724 soatlar
+1677 kunlar
+1 05130 kunlar
Postlar arxiv
Do you enjoy reading this channel? Perhaps you have thought about placing ads on it? To do this, follow three simple steps: 1) Sign up: https://telega.io/c/machinelearning_deeplearning 2) Top up the balance in a convenient way 3) Create an advertising post If the topic of your post fits our channel, we will publish it with pleasure.

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Python for AI 📌.pdf4.14 MB

You can have a look at these resources for learning prompt engineering: Free course with videos and interactive playground: https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/ Popular Prompt Engineering Techniques summarized: https://www.promptingguide.ai/ Examples for different use cases: https://platform.openai.com/docs/guides/prompt-engineering These do not just apply to ChatGPT, they can be used with any open source LLM. If you want to try these out locally using your LLM of choice, have a look at this, it has the full-code on GitHub as well. https://awinml.github.io/llm-ggml-python/ Join for more: https://t.me/machinelearning_deeplearning ENJOY LEARNING 👍👍

Machine Learning with Decision Trees and Random Forests 📝.pdf1.79 MB

Deep Learning for Finance.pdf9.36 MB

This is how ML works
This is how ML works

Generative AI with Python and TensorFlow 2 Joseph Babcock, 2021

Natural Language Processing in the Real World.pdf25.62 MB

Python Programming Notes 📝

Advanced Python: Practical Database Examples.zip253.86 MB

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Deep Learning Book.pdf5.28 MB

Modern Computer Vision with Pytorch V. Kishore Ayyadevara, 2020

ML Handwritten Notes .pdf.pdf51.70 MB

AI Agents - Build and Host LLM Apps At Scale
AI Agents - Build and Host LLM Apps At Scale

Machine Learning for Decision Makers Patanjali Kashyap, 2023

Tech Community & Referrals Network -> https://t.me/addlist/KBNT2WWRIEs0NzIx All the best 👍👍

Quantum Machine Learning.pdf14.58 MB

Tech Community & Referrals Network -> https://t.me/addlist/KBNT2WWRIEs0NzIx All the best 👍👍

The Gemini Public API is a tool provided by the Gemini cryptocurrency exchange that allows users to place, cancel, and view orders, stream market data, and get account data. The API offers both public and private REST APIs, with the public APIs providing market data such as the current order book, recent trading activity, and trade history. Private APIs allow users to manage both orders and funds, including placing and canceling orders, seeing active orders, and viewing trading history and trade volume. The Gemini API can be accessed via REST, WebSocket, and FIX APIs, and its documentation is available at https://docs.gemini.com/.

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