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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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πŸ“ˆ Analytical overview of Telegram channel Machine Learning with Python

Channel Machine Learning with Python (@codeprogrammer) in the English language segment is an active participant. Currently, the community unites 68 128 subscribers, ranking 2 370 in the Education category and 4 740 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 68 128 subscribers.

According to the latest data from 29 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 67 over the last 30 days and by 13 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 3.98%. Within the first 24 hours after publication, content typically collects 1.55% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 714 views. Within the first day, a publication typically gains 1 053 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 6.
  • Thematic interests: Content is focused on key topics such as insidead, learning, degree, evaluation, algorithm.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œLearn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Thanks to the high frequency of updates (latest data received on 30 August, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

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68 128
Subscribers
+1324 hours
-567 days
+6730 days
Posts Archive
Question: What are Python set comprehensions? Answer:Set comprehensions are similar to list comprehensions but create a set instead of a list. The syntax is:
{expression for item in iterable if condition}
For example, to create a set of squares of even numbers:
squares_set = {x**2 for x in range(10) if x % 2 == 0}
This will create a set with the values
{0, 4, 16, 36, 64}
https://t.me/DataScienceQ 🌟

πŸ€–πŸ§  Agentic Entropy-Balanced Policy Optimization (AEPO): Balancing Exploration and Stability in Reinforcement Learning for W
πŸ€–πŸ§  Agentic Entropy-Balanced Policy Optimization (AEPO): Balancing Exploration and Stability in Reinforcement Learning for Web Agents πŸ—“οΈ 17 Oct 2025 πŸ“š AI News & Trends AEPO (Agentic Entropy-Balanced Policy Optimization) represents a major advancement in the evolution of Agentic Reinforcement Learning (RL). As large language models (LLMs) increasingly act as autonomous web agents – searching, reasoning and interacting with tools – the need for balanced exploration and stability has become crucial. Traditional RL methods often rely heavily on entropy to ... #AgenticRL #ReinforcementLearning #LLMs #WebAgents #EntropyBalanced #PolicyOptimization

πŸ€–πŸ§  NVIDIA, MIT, HKU and Tsinghua University Introduce QeRL: A Powerful Quantum Leap in Reinforcement Learning for LLMs πŸ—“οΈ
πŸ€–πŸ§  NVIDIA, MIT, HKU and Tsinghua University Introduce QeRL: A Powerful Quantum Leap in Reinforcement Learning for LLMs πŸ—“οΈ 17 Oct 2025 πŸ“š AI News & Trends The rise of large language models (LLMs) has redefined artificial intelligence powering everything from conversational AI to autonomous reasoning systems. However, training these models especially through reinforcement learning (RL) is computationally expensive requiring massive GPU resources and long training cycles. To address this, a team of researchers from NVIDIA, Massachusetts Institute of Technology (MIT), The ... #QuantumLearning #ReinforcementLearning #LLMs #NVIDIA #MIT #TsinghuaUniversity

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Contribute with us to expand the services offered in our channel We plan to use an advanced AI model to add more information about the most prominent events, models, and articles released and provide explanations. This requires preparing an infrastructure for our server and purchasing an API for an AI model. Contribute to the development of our community with us Contact me @husseinsheikho

πŸ€–πŸ§  MinerU2.5 by Shanghai AI Lab, Peking University & Shanghai Jiao Tong University Sets New Standard for AI-Powered Documen
πŸ€–πŸ§  MinerU2.5 by Shanghai AI Lab, Peking University & Shanghai Jiao Tong University Sets New Standard for AI-Powered Document Parsing πŸ—“οΈ 15 Oct 2025 πŸ“š AI News & Trends In the world of digital transformation, the ability to accurately extract and interpret information from complex documents is becoming increasingly essential. Whether for academic research, financial analysis or enterprise automation, document parsing – the process of converting structured and unstructured document data into machine-readable formats plays a vital role. Enter MinerU2.5, a groundbreaking vision-language model ...

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β˜„οΈ Top 12 YouTube Channels to Learn Python πŸ’ Python will include 57% of data scientist job ads in 2024 . It is still the number one programming language for data scientists. βœ… Now, if you are looking for the best resources to improve your Python skills, after searching and reviewing various resources, I have prepared a list of 12 top channels that provide first-class Python training, which can turn beginners into professional Python programmers. convert 🎬 Python Programmer channel ─ πŸ“ˆ 211 videos / 465K SUB β”˜ πŸ”΄ Link: Python Programmer 🎬 Luke Barousse channel ─ πŸ“ˆ 157 videos / 429K SUB β”˜ πŸ”΄ Link: Luke Barousse 🎬 codebasics channel ─ πŸ“ˆ 837 videos / 990K SUB β”˜ πŸ”΄ link: codebasics 🎬 StatQuest channel with Josh Starmer ─ πŸ“ˆ 271 videos / 1.14M SUB β”˜ πŸ”΄ Link: StatQuest with Josh Starmer 🎬 Sundas Khalid channel ─ πŸ“ˆ 143 videos / 203K SUB β”˜ πŸ”΄ Link: Sundas Khalid 🎬 Shashank Kalanithi channel ─ πŸ“ˆ 152 videos / 148K SUB β”˜ πŸ”΄ Link: Shashank Kalanithi 🎬 Programming with Mosh channel ─ πŸ“ˆ 203 videos / 3.85M SUB β”˜ πŸ”΄ Link: Programming with Mosh 🎬 Corey Schafer channel ─ πŸ“ˆ 233 videos / 129K SUB β”˜ πŸ”΄ Link: Corey Schafer 🎬 sentdex channel ─ πŸ“ˆ 1254 videos / 1.3M SUB β”˜ πŸ”΄ link: sentdex 🎬 Patrick Loeber channel ─ πŸ“ˆ 206 videos / 264K SUB β”˜ πŸ”΄ Link: Patrick Loeber 🎬 Socratica channel ─ πŸ“ˆ 659 videos / 876K SUB β”˜ πŸ”΄ Link: Socratica 🎬 Tech With Tim channel ─ πŸ“ˆ 983 videos / 1.48M SUB β”˜ πŸ”΄ Link: Tech With Tim 😠 More likes 😠 ➑️ more posts ✈️ http://t.me/codeprogrammer βœ…

Question: What is type hinting in Python, and how does it enhance code quality? Answer: πŸ‘‰

πŸ€–πŸ§  Diffusion Transformers with Representation Autoencoders (RAE): The Next Leap in Generative AI πŸ—“οΈ 14 Oct 2025 πŸ“š AI News
πŸ€–πŸ§  Diffusion Transformers with Representation Autoencoders (RAE): The Next Leap in Generative AI πŸ—“οΈ 14 Oct 2025 πŸ“š AI News & Trends Diffusion Transformers (DiTs) have revolutionized image and video generation enabling stunningly realistic outputs in systems like Stable Diffusion and Imagen. However, despite innovations in transformer architectures and training methods, one crucial element of the diffusion pipeline has remained largely stagnant- the autoencoder that defines the latent space. Most current diffusion models still depend on Variational ... #DiffusionTransformers #RAE #GenerativeAI #StableDiffusion #Imagen #LatentSpace

πŸ€–πŸ§  LLaMAX2 by Nanjing University, HKU, CMU & Shanghai AI Lab: A Breakthrough in Translation-Enhanced Reasoning Models πŸ—“οΈ 1
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πŸ€–πŸ§  Granite-Speech-3.3-8B: IBM’s Next-Gen Speech-Language Model for Enterprise AI πŸ—“οΈ 14 Oct 2025 πŸ“š AI News & Trends In the
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