๐ฅ NEW YEAR 2026 โ PREMIUM SCIENTIFIC PAPER WRITING OFFER ๐ฅ
Q1-Ready | Journal-Targeted | Publication-Focused
Serious researchers, PhD & MSc students, postdocs, universities, and funded startups only.
To start 2026 strong, weโre offering a limited New Year scientific writing package designed for fast-track publication, not academic busywork.
๐ฏ What We Offer (End-of-Year Special):
โ๏ธ Full Research Paper Writing โ $400
(Q1 / Q2 journalโready)
Includes:
โ Journal-targeted manuscript (Elsevier / Springer / Wiley / IEEE / MDPI)
โ IMRAD structure (IntroductionโMethodsโResultsโDiscussion)
โ Strong problem formulation & novelty framing
โ Methodology written to reviewer standards
โ Professional academic English (native-level)
โ Plagiarism-free (Turnitin <10%)
โ Ready for immediate submission
๐ Available Paper Types:
Original Research Articles
Review & Systematic Review
AI / Machine Learning Papers
Engineering & Medical Research
Health AI & Clinical Data Studies
Interdisciplinary & Applied Research
๐ง Optional Add-ons (if needed):
Journal selection & scope matching
Cover letter to editor
Reviewer response (after review)
Statistical validation & result polishing
Figure & table redesign (publication quality)
๐ Why This Is Different
We donโt โwrite generic papers.โ
We engineer publishable research.
โ๏ธ Real novelty positioning
โ๏ธ Reviewer-proof logic
โ๏ธ Data-driven arguments
โ๏ธ Aligned with current 2025โ2026 journal expectations
Many of our papers are built on real-world datasets and are already aligned with Q1 journal standards.
โณ New Year Offer โ Limited Time
Regular price: $1,500 โ $3,000
New Year 2026 price: $400
Limited slots (quality > quantity)
๐ Priority given to:
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Active researchers
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Universities & labs
๐ฉ DM for details, samples & timelines
Contact:
@Omidyzd62
Start 2026 with a submitted paperโnot just a plan
Q1-Ready | Journal-Targeted | Publication-Focused
Serious researchers, PhD & MSc students, postdocs, universities, and funded startups only.
To start 2026 strong, weโre offering a limited New Year scientific writing package designed for fast-track publication, not academic busywork.
๐ฏ What We Offer (End-of-Year Special):
โ๏ธ Full Research Paper Writing โ $400
(Q1 / Q2 journalโready)
Includes:
โ Journal-targeted manuscript (Elsevier / Springer / Wiley / IEEE / MDPI)
โ IMRAD structure (IntroductionโMethodsโResultsโDiscussion)
โ Strong problem formulation & novelty framing
โ Methodology written to reviewer standards
โ Professional academic English (native-level)
โ Plagiarism-free (Turnitin <10%)
โ Ready for immediate submission
๐ Available Paper Types:
Original Research Articles
Review & Systematic Review
AI / Machine Learning Papers
Engineering & Medical Research
Health AI & Clinical Data Studies
Interdisciplinary & Applied Research
๐ง Optional Add-ons (if needed):
Journal selection & scope matching
Cover letter to editor
Reviewer response (after review)
Statistical validation & result polishing
Figure & table redesign (publication quality)
๐ Why This Is Different
We donโt โwrite generic papers.โ
We engineer publishable research.
โ๏ธ Real novelty positioning
โ๏ธ Reviewer-proof logic
โ๏ธ Data-driven arguments
โ๏ธ Aligned with current 2025โ2026 journal expectations
Many of our papers are built on real-world datasets and are already aligned with Q1 journal standards.
โณ New Year Offer โ Limited Time
Regular price: $1,500 โ $3,000
New Year 2026 price: $400
Limited slots (quality > quantity)
๐ Priority given to:
PhD / MSc students
Active researchers
Funded startups
Universities & labs
๐ฉ DM for details, samples & timelines
Contact:
@Omidyzd62
Start 2026 with a submitted paperโnot just a plan
โค6๐ฅ3
Machine Learning with Python pinned ยซ๐ฅ NEW YEAR 2026 โ PREMIUM SCIENTIFIC PAPER WRITING OFFER ๐ฅ Q1-Ready | Journal-Targeted | Publication-Focused Serious researchers, PhD & MSc students, postdocs, universities, and funded startups only. To start 2026 strong, weโre offering a limited New Yearโฆยป
Forwarded from Machine Learning with Python
๐Stanford just completed a must-watch for anyone serious about AI:
๐ โ๐๐ ๐ ๐ฎ๐ต๐ฑ: ๐ง๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ๐ฒ๐ฟ๐ & ๐๐ฎ๐ฟ๐ด๐ฒ ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐ ๐ผ๐ฑ๐ฒ๐น๐โ is now live entirely on YouTube and itโs pure gold.
If youโre building your AI career, stop scrolling.
This isnโt another surface-level overview. Itโs the clearest, most structured intro to LLMs you could follow, straight from the Stanford Autumn 2025 curriculum.
๐ ๐ง๐ผ๐ฝ๐ถ๐ฐ๐ ๐ฐ๐ผ๐๐ฒ๐ฟ๐ฒ๐ฑ ๐ถ๐ป๐ฐ๐น๐๐ฑ๐ฒ:
โข How Transformers actually work (tokenization, attention, embeddings)
โข Decoding strategies & MoEs
โข LLM finetuning (LoRA, RLHF, supervised)
โข Evaluation techniques (LLM-as-a-judge)
โข Optimization tricks (RoPE, quantization, approximations)
โข Reasoning & scaling
โข Agentic workflows (RAG, tool calling)
๐ง My workflow: I usually take the transcripts, feed them into NotebookLM, and once Iโve done the lectures, I replay them during walks or commutes. That combo works wonders for retention.
๐ฅ Watch these now:
- Lecture 1: https://lnkd.in/dDER-qyp
- Lecture 2: https://lnkd.in/dk-tGUDm
- Lecture 3: https://lnkd.in/drAPdjJY
- Lecture 4: https://lnkd.in/e_RSgMz7
- Lecture 5: https://lnkd.in/eivMA9pe
- Lecture 6: https://lnkd.in/eYwwwMXn
- Lecture 7: https://lnkd.in/eKwkEDXV
- Lecture 8: https://lnkd.in/eEWvyfyK
- Lecture 9: https://lnkd.in/euiKRGaQ
๐ Do yourself a favor for this 2026: block 2-3 hours per week / llectue and go through them.
If youโre in AI โ whether building infra, agents, or apps โ this is the foundational course you donโt want to miss.
Letโs level up.
https://t.me/CodeProgrammer๐
๐ โ๐๐ ๐ ๐ฎ๐ต๐ฑ: ๐ง๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ๐ฒ๐ฟ๐ & ๐๐ฎ๐ฟ๐ด๐ฒ ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐ ๐ผ๐ฑ๐ฒ๐น๐โ is now live entirely on YouTube and itโs pure gold.
If youโre building your AI career, stop scrolling.
This isnโt another surface-level overview. Itโs the clearest, most structured intro to LLMs you could follow, straight from the Stanford Autumn 2025 curriculum.
๐ ๐ง๐ผ๐ฝ๐ถ๐ฐ๐ ๐ฐ๐ผ๐๐ฒ๐ฟ๐ฒ๐ฑ ๐ถ๐ป๐ฐ๐น๐๐ฑ๐ฒ:
โข How Transformers actually work (tokenization, attention, embeddings)
โข Decoding strategies & MoEs
โข LLM finetuning (LoRA, RLHF, supervised)
โข Evaluation techniques (LLM-as-a-judge)
โข Optimization tricks (RoPE, quantization, approximations)
โข Reasoning & scaling
โข Agentic workflows (RAG, tool calling)
๐ง My workflow: I usually take the transcripts, feed them into NotebookLM, and once Iโve done the lectures, I replay them during walks or commutes. That combo works wonders for retention.
๐ฅ Watch these now:
- Lecture 1: https://lnkd.in/dDER-qyp
- Lecture 2: https://lnkd.in/dk-tGUDm
- Lecture 3: https://lnkd.in/drAPdjJY
- Lecture 4: https://lnkd.in/e_RSgMz7
- Lecture 5: https://lnkd.in/eivMA9pe
- Lecture 6: https://lnkd.in/eYwwwMXn
- Lecture 7: https://lnkd.in/eKwkEDXV
- Lecture 8: https://lnkd.in/eEWvyfyK
- Lecture 9: https://lnkd.in/euiKRGaQ
๐ Do yourself a favor for this 2026: block 2-3 hours per week / llectue and go through them.
If youโre in AI โ whether building infra, agents, or apps โ this is the foundational course you donโt want to miss.
Letโs level up.
https://t.me/CodeProgrammer
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Forwarded from Code With Python
Automatic translator in Python!
We translate a text in a few lines using
Install the library:
Example of use:
Mass translation of a list:
๐ฅ We get a mini-Google Translate right in Python: you can embed it in a chatbot, use it in notes, or automate work with the API.
๐ช @DataScience4
We translate a text in a few lines using
deep-translator. It supports dozens of languages: from English and Russian to Japanese and Arabic.Install the library:
pip install deep-translator
Example of use:
from deep_translator import GoogleTranslator
text = "Hello, how are you?"
result = GoogleTranslator(source="ru", target="en").translate(text)
print("Original:", text)
print("Translation:", result)
Mass translation of a list:
texts = ["Hello", "What's your name?", "See you later"]
for t in texts:
print("โ", GoogleTranslator(source="ru", target="es").translate(t))
๐ฅ We get a mini-Google Translate right in Python: you can embed it in a chatbot, use it in notes, or automate work with the API.
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In scientific work, the most time is spent on reading articles, data, and reports.
On GitHub, there is a collection called Awesome AI for Science -ยปยปยป a catalog of AI tools for all stages of research.
Inside:
-ยป working with literature
-ยป data analysis
-ยป turning articles into posters
-ยป automating experiments
-ยป tools for biology, chemistry, physics, and other fields
GitHub: http://github.com/ai-boost/awesome-ai-for-science
The list includes Paper2Poster, MinerU, The AI Scientist, as well as articles, datasets, and frameworks.
In fact, this is a complete set of tools for AI support in scientific research.
๐ https://t.me/CodeProgrammer
On GitHub, there is a collection called Awesome AI for Science -ยปยปยป a catalog of AI tools for all stages of research.
Inside:
-ยป working with literature
-ยป data analysis
-ยป turning articles into posters
-ยป automating experiments
-ยป tools for biology, chemistry, physics, and other fields
GitHub: http://github.com/ai-boost/awesome-ai-for-science
The list includes Paper2Poster, MinerU, The AI Scientist, as well as articles, datasets, and frameworks.
In fact, this is a complete set of tools for AI support in scientific research.
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AI-ML Roadmap from Scratch
๐ https://github.com/aadi1011/AI-ML-Roadmap-from-scratch?tab=readme-ov-file
https://t.me/CodeProgrammer๐
Like and Share
https://t.me/CodeProgrammer
Like and Share
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๐ Master Data Science & Programming!
Unlock your potential with this curated list of Telegram channels. Whether you need books, datasets, interview prep, or project ideas, we have the perfect resource for you. Join the community today!
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Admin: @HusseinSheikho
Unlock your potential with this curated list of Telegram channels. Whether you need books, datasets, interview prep, or project ideas, we have the perfect resource for you. Join the community today!
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
https://t.me/CodeProgrammer
Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.
https://t.me/DataScienceM
This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA โ perfect for learning, coding, and mastering key programming skills.
https://t.me/DataScience4
Python Data Science jobs, interview tips, and career insights for aspiring professionals.
https://t.me/DataScienceQ
Your go-to hub for Kaggle datasets โ explore, analyze, and leverage data for Machine Learning and Data Science projects.
https://t.me/datasets1
The first channel in Telegram that offers free Udemy coupons
https://t.me/DataScienceC
Advancing research in Machine Learning โ practical insights, tools, and techniques for researchers.
https://t.me/DataScienceT
An active community group for discussing data challenges and networking with peers.
https://t.me/DataScience9
The largest Arabic-speaking group for Python developers to share knowledge and help.
https://t.me/PythonArab
Explore the world of Data Science through Jupyter Notebooksโinsights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
https://t.me/DataScienceN
Free online courses covering data science, machine learning, analytics, programming, and essential skills for learners.
https://t.me/DataScienceV
Dive into the world of Data Analytics โ uncover insights, explore trends, and master data-driven decision making.
https://t.me/DataAnalyticsX
Master Python with step-by-step courses โ from basics to advanced projects and practical applications.
https://t.me/Python53
Professional Academic Writing & Simulation Services
https://t.me/DataScienceY
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