π LLM Scraper β parsing websites through neural networks
The tool allows you to convert any web pages into structured data using LLM.
Useful for data collection, site monitoring, and preparing datasets without writing complex parsers.
βοΈ Link to GitHub: https://github.com/mishushakov/llm-scraper
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
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#LLM #Scraper #WebScraping #DataCollection #AI #Automation
The tool allows you to convert any web pages into structured data using LLM.
Useful for data collection, site monitoring, and preparing datasets without writing complex parsers.
βοΈ Link to GitHub: https://github.com/mishushakov/llm-scraper
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
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Forwarded from Machine Learning with Python
A new collection of free courses has been added:
π https://github.com/dair-ai/ML-Course-Notes
Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. π
Machine Learning Course Notes is an open collection of notes on machine learning, NLP, and AI, compiled around full-fledged courses, not just individual videos. π§
What's inside:
β’ Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
β’ A table with lectures, descriptions, videos, notes, and authors
β’ Links to the original lectures and accompanying notes
β’ WIP markers for incomplete materials
β’ Instructions for contributors on adding and improving notes
The idea was appreciated. π
Instead of another collection of hundreds of links, a course map has been created where one can systematically go through the material without getting lost after a week of studying. πΊοΈ
#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
π https://github.com/dair-ai/ML-Course-Notes
Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. π
Machine Learning Course Notes is an open collection of notes on machine learning, NLP, and AI, compiled around full-fledged courses, not just individual videos. π§
What's inside:
β’ Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
β’ A table with lectures, descriptions, videos, notes, and authors
β’ Links to the original lectures and accompanying notes
β’ WIP markers for incomplete materials
β’ Instructions for contributors on adding and improving notes
The idea was appreciated. π
Instead of another collection of hundreds of links, a course map has been created where one can systematically go through the material without getting lost after a week of studying. πΊοΈ
#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
GitHub
GitHub - dair-ai/ML-Course-Notes: π Sharing machine learning course / lecture notes.
π Sharing machine learning course / lecture notes. - dair-ai/ML-Course-Notes
β€1
Stop studying LLM from random articles and videos that only explain individual pieces of the puzzle.
π LLM from Scratch β this is a practical course on PyTorch for those who want to understand the entire path of modern LLMs: from the first Transformer block to RLHF.
Instead of endless theory, here we gather a complete model training chain:
πΉ Pretraining β Finetuning β Alignment in one course
πΉ Transformer from scratch: positional embeddings, self-attention, multi-head attention, MLP, residual connections, LayerNorm, and full Transformer blocks
πΉ Own training loop without Trainer magic: tokenization, batches, cross-entropy, validation loss, text generation
πΉ Modern architecture improvements: RMSNorm, RoPE, SwiGLU, KV Cache, sliding-window attention, and streaming cache
πΉ Full section on alignment: SFT, reward models, PPO-style RLHF, and GRPO with an analysis of how it looks in the training loop in practice
https://github.com/vivekkalyanarangan30/llm_from_scratch
#LLM #PyTorch #MachineLearning #DeepLearning #AI #Transformer
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
π LLM from Scratch β this is a practical course on PyTorch for those who want to understand the entire path of modern LLMs: from the first Transformer block to RLHF.
Instead of endless theory, here we gather a complete model training chain:
πΉ Pretraining β Finetuning β Alignment in one course
πΉ Transformer from scratch: positional embeddings, self-attention, multi-head attention, MLP, residual connections, LayerNorm, and full Transformer blocks
πΉ Own training loop without Trainer magic: tokenization, batches, cross-entropy, validation loss, text generation
πΉ Modern architecture improvements: RMSNorm, RoPE, SwiGLU, KV Cache, sliding-window attention, and streaming cache
πΉ Full section on alignment: SFT, reward models, PPO-style RLHF, and GRPO with an analysis of how it looks in the training loop in practice
https://github.com/vivekkalyanarangan30/llm_from_scratch
#LLM #PyTorch #MachineLearning #DeepLearning #AI #Transformer
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βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
β€2
Forwarded from Machine Learning with Python
Kaggle and Google are launching a free 5-day intensive course on VibeCoding. π
Over five days, they will explain how agent-based coding works, how to configure skills, memory, and context, and how to make AI assistants not only useful but also safe. π€ The program includes daily tasks, live streams, discussions, and practical projects. π»
After completion, participants will receive an official certificate that can be added to their portfolio. π
Start date: June 15th. π
https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google π
If you've long wanted to properly understand agent-based coding, this is a great opportunity to dive in. π
#Kaggle #Google #VibeCoding #AIAgents #Coding #AI #TechNews #FreeCourse
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Over five days, they will explain how agent-based coding works, how to configure skills, memory, and context, and how to make AI assistants not only useful but also safe. π€ The program includes daily tasks, live streams, discussions, and practical projects. π»
After completion, participants will receive an official certificate that can be added to their portfolio. π
Start date: June 15th. π
https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google π
If you've long wanted to properly understand agent-based coding, this is a great opportunity to dive in. π
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βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Forwarded from Machine Learning with Python
π SPOTO Mid-Year Sale β Grab Your IT Certification Success Kit!
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β Free Resources:
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π Join SPOTO Mid-Year Lucky Draw:
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π Enter the Draw Now β https://bit.ly/4uN3lVt
π Join Our IT Learning Community for free resources & support:
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π¬ Want exam help? Chat with an admin now:
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β° Mid-Year Deal Ends Soon β Don't Miss Out!
π₯ Whether you're prepping for #Python, #AI, #Cisco, #PMI, #Fortinet, #AWS, #Azure, #Excel, #Comptia, #ITIL, #Cloud or any other hot certification β SPOTO has your back with real exam dumps and hands-on training!
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γ»Free Cloud Study Guide: https://bit.ly/4u7sdG0
π Join SPOTO Mid-Year Lucky Draw:
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π Amazon Gift $100 πPMP/ AWS/ CCNA Course
π Enter the Draw Now β https://bit.ly/4uN3lVt
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Google has published a free guide on scaling AI models and working with GPUs. π
π How to Scale Your Model
https://jax-ml.github.io/scaling-book/
π How to Think About GPUs
https://jax-ml.github.io/scaling-book/gpus/
The materials discuss the principles of model scaling, the structure of GPUs, computational limitations, memory bandwidth, parallelism, and other topics that are useful when training and running modern AI models. π‘
It's completely free and available online. π
#AI #MachineLearning #GPU #Scaling #DeepLearning #Tech
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
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π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
π How to Scale Your Model
https://jax-ml.github.io/scaling-book/
π How to Think About GPUs
https://jax-ml.github.io/scaling-book/gpus/
The materials discuss the principles of model scaling, the structure of GPUs, computational limitations, memory bandwidth, parallelism, and other topics that are useful when training and running modern AI models. π‘
It's completely free and available online. π
#AI #MachineLearning #GPU #Scaling #DeepLearning #Tech
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
How To Scale Your Model
Training LLMs often feels like alchemy, but understanding and optimizing the performance of your models doesn't have to. This book aims to demystify the science of scaling language models: how TPUs (and GPUs) work and how they communicate with each otherβ¦
β€1
Forwarded from Machine Learning with Python
10 GitHub repositories that are worth checking out for an AI engineer π€
1. Hands-On AI Engineering π οΈ
A collection of AI applications and agent systems with practical use cases of LLM.
π https://github.com/Sumanth077/Hands-On-AI-Engineering
2. Hands-On Large Language Models π
Full code from the book Hands-On Large Language Models: from basics to fine-tuning.
π https://github.com/HandsOnLLM/Hands-On-Large-Language-Models
3. AI Agents for Beginners π
A free course from Microsoft with 11 lessons on creating AI agents.
π https://github.com/microsoft/ai-agents-for-beginners
4. GenAI Agents π€
A large collection of tutorials and implementations of agent systems.
π https://github.com/NirDiamant/GenAI_Agents
5. Made With ML π
About the development, deployment, and support of production-ready ML systems.
π https://github.com/GokuMohandas/Made-With-ML
6. Learn Harness Engineering βοΈ
A practical course on Harness Engineering for AI agents.
π https://github.com/walkinglabs/learn-harness-engineering
7. AutoResearch π¬
Autonomous cycles of ML experiments from Andrej Karpathy.
π https://github.com/karpathy/autoresearch
8. Designing Machine Learning Systems π
Notes and materials from Chip Huyen's book.
π https://github.com/chiphuyen/dmls-book
9. Awesome LLM Inference β‘
A collection of materials on LLM inference: Flash Attention, KV Cache, quantization, and more.
π https://github.com/xlite-dev/Awesome-LLM-Inference
10. LLM Course πΊοΈ
A practical course on LLM with a roadmap and Colab notebooks.
π https://github.com/mlabonne/llm-course
#AI #MachineLearning #LLM #DataScience #Tech #GitHub
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
1. Hands-On AI Engineering π οΈ
A collection of AI applications and agent systems with practical use cases of LLM.
π https://github.com/Sumanth077/Hands-On-AI-Engineering
2. Hands-On Large Language Models π
Full code from the book Hands-On Large Language Models: from basics to fine-tuning.
π https://github.com/HandsOnLLM/Hands-On-Large-Language-Models
3. AI Agents for Beginners π
A free course from Microsoft with 11 lessons on creating AI agents.
π https://github.com/microsoft/ai-agents-for-beginners
4. GenAI Agents π€
A large collection of tutorials and implementations of agent systems.
π https://github.com/NirDiamant/GenAI_Agents
5. Made With ML π
About the development, deployment, and support of production-ready ML systems.
π https://github.com/GokuMohandas/Made-With-ML
6. Learn Harness Engineering βοΈ
A practical course on Harness Engineering for AI agents.
π https://github.com/walkinglabs/learn-harness-engineering
7. AutoResearch π¬
Autonomous cycles of ML experiments from Andrej Karpathy.
π https://github.com/karpathy/autoresearch
8. Designing Machine Learning Systems π
Notes and materials from Chip Huyen's book.
π https://github.com/chiphuyen/dmls-book
9. Awesome LLM Inference β‘
A collection of materials on LLM inference: Flash Attention, KV Cache, quantization, and more.
π https://github.com/xlite-dev/Awesome-LLM-Inference
10. LLM Course πΊοΈ
A practical course on LLM with a roadmap and Colab notebooks.
π https://github.com/mlabonne/llm-course
#AI #MachineLearning #LLM #DataScience #Tech #GitHub
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Forwarded from Machine Learning with Python
Learn AI for free directly from top companies. π
1 - Anthropic:
anthropic.skilljar.com
2 - Google:
grow.google/ai
3 - Meta:
ai.meta.com/resources/
4 - NVIDIA:
developer.nvidia.com/cuda
5 - Microsoft:
learn.microsoft.com/en-us/training/
6 - OpenAI:
academy.openai.com
7 - IBM:
skillsbuild.org
8 - AWS:
skillbuilder.aws
9 - DeepLearning.AI:
deeplearning.ai
10 - Hugging Face:
huggingface.co/learn
π¬ Comment "Learning" if you find this helpful.
π Repost so others can take help.
π Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://xn--r1a.website/CodeProgrammer
1 - Anthropic:
anthropic.skilljar.com
2 - Google:
grow.google/ai
3 - Meta:
ai.meta.com/resources/
4 - NVIDIA:
developer.nvidia.com/cuda
5 - Microsoft:
learn.microsoft.com/en-us/training/
6 - OpenAI:
academy.openai.com
7 - IBM:
skillsbuild.org
8 - AWS:
skillbuilder.aws
9 - DeepLearning.AI:
deeplearning.ai
10 - Hugging Face:
huggingface.co/learn
π¬ Comment "Learning" if you find this helpful.
π Repost so others can take help.
π Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://xn--r1a.website/CodeProgrammer
Grow with Google US
AI Training to Grow Your Career | Google
Learn all about AI & how to supercharge your work or business. We offer AI courses and tools that will help you build essential AI skills.
β€4
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π Building our own GPT-like model in PyTorch
We've found an excellent repository for those who want to understand how modern LLMs are built under the hood.
Inside β 10 Jupyter notebooks with step-by-step explanations and implementations of key components of language models.
GitHub: https://github.com/analyticalrohit/llms-from-scratch
#PyTorch #LLM #MachineLearning #AI #DeepLearning #DataScience
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
We've found an excellent repository for those who want to understand how modern LLMs are built under the hood.
Inside β 10 Jupyter notebooks with step-by-step explanations and implementations of key components of language models.
GitHub: https://github.com/analyticalrohit/llms-from-scratch
#PyTorch #LLM #MachineLearning #AI #DeepLearning #DataScience
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
β€3
Curates LLM tools and research for scientific discovery π§¬π¬
Repo: https://github.com/HKUST-KnowComp/Awesome-LLM-Scientific-Discovery ππ
#LLM #ScientificDiscovery #ResearchTools #AI #MachineLearning #DataScience
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Repo: https://github.com/HKUST-KnowComp/Awesome-LLM-Scientific-Discovery ππ
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
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Attention Heatmap vs Token Pruning πβοΈ
π More: https://www.overshoot.ai/blogs/an-introduction-to-token-pruning-for-vlms
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π Instructions for AI Agents
Please refer to AGENTS.md β a guide dedicated to the file of the same name, which contains instructions for AI agents. π€
The website explains what should be included in AGENTS.md, how to format it correctly, and provides examples from over 60,000 projects. π
http://AGENTS.md/
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Please refer to AGENTS.md β a guide dedicated to the file of the same name, which contains instructions for AI agents. π€
The website explains what should be included in AGENTS.md, how to format it correctly, and provides examples from over 60,000 projects. π
http://AGENTS.md/
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π π€ Run Your Own LOCAL LLM (Beginner Friendly)
LLMs are cool, but running your own local one hits different π
No cloud. No API keys. No limits.
𧩠Step 1: Install Ollama
Install Ollama on your machine (works on Mac, Windows, Linux).
Once installed, open your terminal.
π Step 2: Run a model
This command:
β’ Downloads the model
β’ Starts it locally
β’ Lets you chat instantly π¬
If you see the prompt, your local LLM is running.
βοΈ Step 3: Do local inference (API style)
Ollama runs a local server on your machine.
If you get a JSON response with text β β it works.
π‘ Why this is powerful
β’ Works offline
β’ Private by default
β’ Perfect for learning, testing, and small apps
This is the easiest way to start with LLMs locally.
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#LLM #AI #LocalLLM #Ollama #Tech #Linux
LLMs are cool, but running your own local one hits different π
No cloud. No API keys. No limits.
𧩠Step 1: Install Ollama
Install Ollama on your machine (works on Mac, Windows, Linux).
Once installed, open your terminal.
π Step 2: Run a model
ollama run llama3.2
This command:
β’ Downloads the model
β’ Starts it locally
β’ Lets you chat instantly π¬
If you see the prompt, your local LLM is running.
βοΈ Step 3: Do local inference (API style)
Ollama runs a local server on your machine.
curl http://127.0.0.1:11434/api/generate \
-H "Content-Type: application/json" \
-d '{
"model": "llama3.2",
"prompt": "Explain overfitting like I am 12",
"stream": false
}'
If you get a JSON response with text β β it works.
π‘ Why this is powerful
β’ Works offline
β’ Private by default
β’ Perfect for learning, testing, and small apps
This is the easiest way to start with LLMs locally.
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πStruggling with tough interview questions? Nervous about technical grilling? You're not alone.
We've just released a bunch of 100% free interview prep kits for 2026 β covering common Q&As, behavioral questions, technical deep-dives, and role-specific tips for #Cisco, #AWS, #PMP, #AI, #Python, #Excel, and #Cybersecurity.
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A Collection of Machine Learning Libraries for Python π€
A large repository containing over 900 libraries and frameworks for machine learning. π
All projects are sorted by quality and popularity, which helps you quickly find the best tools for working with AI and ML. βοΈ
Repo: https://github.com/ml-tooling/best-of-ml-python?tab=readme-ov-file#vector-similarity-search-ann
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A large repository containing over 900 libraries and frameworks for machine learning. π
All projects are sorted by quality and popularity, which helps you quickly find the best tools for working with AI and ML. βοΈ
Repo: https://github.com/ml-tooling/best-of-ml-python?tab=readme-ov-file#vector-similarity-search-ann
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π 10 GitHub repositories that are gaining the most traction right now
Here's a fresh selection of projects that are experiencing significant growth and active discussion.
1. OpenAI Codex
An OpenAI coding agent for the terminal and development automation.
https://github.com/openai/codex
2. God's Eye View
OSINT and open geospatial data on an interactive 3D globe: aviation, satellites, and other sources.
https://github.com/bilawalsidhu/gods-eye-view
3. awesome-gpt-image-2
A large library of prompts, examples, and templates for GPT Image 2.
https://github.com/freestylefly/awesome-gpt-image-2
4. mattpocock/skills
Ready-made skills and workflows for coding agents that can be reused instead of using large prompts.
https://github.com/mattpocock/skills
5. Archify
Builds an interactive map of the codebase architecture: sequence, data flow, lifecycle, and component relationships.
https://github.com/tt-a1i/archify
6. Tailcat
A tool from Tailscale for directly connecting machines via WireGuard and NAT traversal.
https://github.com/tailscale/tailcat
7. Prime Agent
A self-improving coding agent for long, autonomous tasks.
https://github.com/PrimeIntellect-ai/prime-agent
8. Semantica
A graph-native infrastructure for storing context, relationships, and data provenance in AI systems.
https://github.com/semantica-agi/semantica
9. Cursor Plugins
The official repository of Cursor plugins: orchestration, code review, continual learning, and other agent functions.
https://github.com/cursor/plugins
10. AnyDoc
A tool from Firecrawl for converting documents into structured content for AI and RAG.
https://github.com/firecrawl/anydoc
π Looking at the overall trend for the week:
AI agents β agent skills β memory and context β visualization of architecture β tools for autonomous work with the environment
πΎ Save this for yourself so you don't lose it!
#GitHub #AI #DevTools #OpenSource #Coding #TechTrends
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Here's a fresh selection of projects that are experiencing significant growth and active discussion.
1. OpenAI Codex
An OpenAI coding agent for the terminal and development automation.
https://github.com/openai/codex
2. God's Eye View
OSINT and open geospatial data on an interactive 3D globe: aviation, satellites, and other sources.
https://github.com/bilawalsidhu/gods-eye-view
3. awesome-gpt-image-2
A large library of prompts, examples, and templates for GPT Image 2.
https://github.com/freestylefly/awesome-gpt-image-2
4. mattpocock/skills
Ready-made skills and workflows for coding agents that can be reused instead of using large prompts.
https://github.com/mattpocock/skills
5. Archify
Builds an interactive map of the codebase architecture: sequence, data flow, lifecycle, and component relationships.
https://github.com/tt-a1i/archify
6. Tailcat
A tool from Tailscale for directly connecting machines via WireGuard and NAT traversal.
https://github.com/tailscale/tailcat
7. Prime Agent
A self-improving coding agent for long, autonomous tasks.
https://github.com/PrimeIntellect-ai/prime-agent
8. Semantica
A graph-native infrastructure for storing context, relationships, and data provenance in AI systems.
https://github.com/semantica-agi/semantica
9. Cursor Plugins
The official repository of Cursor plugins: orchestration, code review, continual learning, and other agent functions.
https://github.com/cursor/plugins
10. AnyDoc
A tool from Firecrawl for converting documents into structured content for AI and RAG.
https://github.com/firecrawl/anydoc
π Looking at the overall trend for the week:
AI agents β agent skills β memory and context β visualization of architecture β tools for autonomous work with the environment
πΎ Save this for yourself so you don't lose it!
#GitHub #AI #DevTools #OpenSource #Coding #TechTrends
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
GitHub
GitHub - openai/codex: Lightweight coding agent that runs in your terminal
Lightweight coding agent that runs in your terminal - openai/codex
β€3
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π₯The 2026 hiring market is shifting fast. We've put together a 100% free resource bundle covering #Cisco, #AWS, #PMP, #AI, #Python, #Excel, and #Cybersecurity β including:
β Q&A banks & mock exams
β Behavioral interview guides
β Technical deep-dives for coding & infrastructure roles
β Real-world project scenarios
Perfect for Software Developer Jobs, IT Internships, and Python Projects practice.
π― Interview Question Bank β https://bit.ly/4A6m0hM
πͺ Online Free Course For Python & Excelβhttps://bit.ly/46bUzWm
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Tag a friend who's job-hunting or grinding Python projects β let's ace it together! πͺ
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