PyTorch in One Hour: From Tensors to Training Neural Networks on Multiple GPUs
This tutorial offers a fast-paced introduction to PyTorch, covering key topics like tensors, GPU training, and backpropagation in about one hour. Its goal is to help you quickly start building and training deep neural networks, including large language models.
https://sebastianraschka.com/teaching/pytorch-1h/
This tutorial offers a fast-paced introduction to PyTorch, covering key topics like tensors, GPU training, and backpropagation in about one hour. Its goal is to help you quickly start building and training deep neural networks, including large language models.
https://sebastianraschka.com/teaching/pytorch-1h/
Sebastian Raschka, PhD
PyTorch in One Hour: From Tensors to Training Neural Networks on Multiple GPUs
A curated introduction to PyTorch that gets you up to speed in about an hour.
Python Gotcha: Reusing Generators Returns Nothing
Reusing a Python generator after it’s been consumed yields no results, because generators maintain state and don’t reset once iterated. The fix is straightforward: call the generator function again to produce a fresh iterator before reusing it.<br>
https://andrewwegner.com/python-gotcha-reusing-generator-returns-nothing.html
Reusing a Python generator after it’s been consumed yields no results, because generators maintain state and don’t reset once iterated. The fix is straightforward: call the generator function again to produce a fresh iterator before reusing it.<br>
https://andrewwegner.com/python-gotcha-reusing-generator-returns-nothing.html
Ponderings of an Andy
Python Gotcha: Reusing Generators Returns Nothing
Generators provide lazy evaluation for processing large datasets efficiently. However, once a generator is exhausted through iteration, it cannot be reused or reset. Let's cover this common gotcha that trips up developers new to this Python feature.
Superfunctions: A universal solution against sync/async fragmentation in Python
https://github.com/pomponchik/transfunctions
https://github.com/pomponchik/transfunctions
GitHub
GitHub - pomponchik/transfunctions: Say NO to Python fragmentation on sync and async
Say NO to Python fragmentation on sync and async. Contribute to pomponchik/transfunctions development by creating an account on GitHub.
Sniffly
Claude Code dashboard with usage stats, error analysis, and sharable feature.
https://github.com/chiphuyen/sniffly
Claude Code dashboard with usage stats, error analysis, and sharable feature.
https://github.com/chiphuyen/sniffly
GitHub
GitHub - chiphuyen/sniffly: Claude Code dashboard with usage stats, error analysis, and sharable feature
Claude Code dashboard with usage stats, error analysis, and sharable feature - chiphuyen/sniffly
Python AI Agents: Overview to Generative AI and Intro to Agents
Glenn Mossy, an AI Solutions Architect, presents an overview of generative AI and introduces Python AI agents, discussing how these technologies are automating tasks and transforming industries, with specific examples including an advanced calculator agent and a file system organizer. The session aims to be accessible for both beginners and experienced coders, highlighting the ongoing ev...
https://www.youtube.com/watch?v=2JPazei9e9Q
Glenn Mossy, an AI Solutions Architect, presents an overview of generative AI and introduces Python AI agents, discussing how these technologies are automating tasks and transforming industries, with specific examples including an advanced calculator agent and a file system organizer. The session aims to be accessible for both beginners and experienced coders, highlighting the ongoing ev...
https://www.youtube.com/watch?v=2JPazei9e9Q
YouTube
Python AI Agents: Overview to Generative AI and Intro to Agents
Glenn will start by providing an overview of Generative AI, a groundbreaking technology that enables machines to produce human-like text, images, and even code. This innovation is transforming various industries by automating tasks, enhancing creativity,…
UQLM
UQLM is a Python library for Large Language Model (LLM) hallucination detection using state-of-the-art uncertainty quantification techniques.
https://github.com/cvs-health/uqlm
UQLM is a Python library for Large Language Model (LLM) hallucination detection using state-of-the-art uncertainty quantification techniques.
https://github.com/cvs-health/uqlm
GitHub
GitHub - cvs-health/uqlm: UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination…
UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection - cvs-health/uqlm
UV is helping me slowly get rid of bad practices and improve company’s internal tooling.
https://www.reddit.com/r/Python/comments/1mcgsxr/uv_is_helping_me_slowly_get_rid_of_bad_practices/
https://www.reddit.com/r/Python/comments/1mcgsxr/uv_is_helping_me_slowly_get_rid_of_bad_practices/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
QwenLM / Qwen3-Coder
Qwen3-Coder is the code version of Qwen3, the large language model series developed by Qwen team, Alibaba Cloud.
https://github.com/QwenLM/Qwen3-Coder
Qwen3-Coder is the code version of Qwen3, the large language model series developed by Qwen team, Alibaba Cloud.
https://github.com/QwenLM/Qwen3-Coder
GitHub
GitHub - QwenLM/Qwen3-Coder: Qwen3-Coder is the code version of Qwen3, the large language model series developed by Qwen team,…
Qwen3-Coder is the code version of Qwen3, the large language model series developed by Qwen team, Alibaba Cloud. - QwenLM/Qwen3-Coder
Fully Homomorphic Encryption and the Dawn of A Truly Private Internet
Fully Homomorphic Encryption (FHE) allows computation on encrypted data and is becoming ~8× faster each year. It could enable a privacy-by-default internet, powering secure cloud and AI services without exposing user data.
https://bozmen.io/fhe
Fully Homomorphic Encryption (FHE) allows computation on encrypted data and is becoming ~8× faster each year. It could enable a privacy-by-default internet, powering secure cloud and AI services without exposing user data.
https://bozmen.io/fhe
Fully Homomorphic Encryption and the Dawn of A Truly Private Internet
Barış Özmen Blog
A Python dict that can report which keys you did not use
https://www.peterbe.com/plog/a-python-dict-that-can-report-which-keys-you-did-not-use
https://www.peterbe.com/plog/a-python-dict-that-can-report-which-keys-you-did-not-use
Peterbe
A Python dict that can report which keys you did not use - Peterbe.com
Demonstrates a very basic way, in Python, how to know which fields of a dict you never accessed.
passage-of-time-mcp
An MCP server that gives language models temporal awareness and time calculation abilities. Teaching AI the significance of the passage of time through collaborative tool development.
https://github.com/jlumbroso/passage-of-time-mcp
An MCP server that gives language models temporal awareness and time calculation abilities. Teaching AI the significance of the passage of time through collaborative tool development.
https://github.com/jlumbroso/passage-of-time-mcp
GitHub
GitHub - jlumbroso/passage-of-time-mcp: 🤖🕰️ An MCP server that gives language models temporal awareness and time calculation abilities.…
🤖🕰️ An MCP server that gives language models temporal awareness and time calculation abilities. Teaching AI the significance of the passage of time through collaborative tool development. - jlumbro...
3 pandas Workflows That Slowed to a Crawl on Large Datasets—Until We Turned on GPUs
NVIDIA shows how switching from pandas to GPU-accelerated cuDF made slow data workflows run up to 30× faster. Common tasks like time-series analysis and dashboard filtering became near-instant with minimal code changes.
https://developer.nvidia.com/blog/3-pandas-workflows-that-slowed-to-a-crawl-on-large-datasets-until-we-turned-on-gpus/
NVIDIA shows how switching from pandas to GPU-accelerated cuDF made slow data workflows run up to 30× faster. Common tasks like time-series analysis and dashboard filtering became near-instant with minimal code changes.
https://developer.nvidia.com/blog/3-pandas-workflows-that-slowed-to-a-crawl-on-large-datasets-until-we-turned-on-gpus/
NVIDIA Technical Blog
3 pandas Workflows That Slowed to a Crawl on Large Datasets—Until We Turned on GPUs
If you work with pandas, you’ve probably hit the wall. It’s that moment when your trusty workflow, so elegant on smaller datasets, grinds to a halt on a large one. A script that once took seconds now…
Announcing Toad - a universal UI for agentic coding in the terminal
Will McGugan announces Toad, a new universal terminal UI for AI coding agents built with Textual, offering a flicker-free and interactive experience compared to existing tools. Toad will be open source, supports any backend language, and uses JSON for communication between frontend and backend.
https://willmcgugan.github.io/announcing-toad/
Will McGugan announces Toad, a new universal terminal UI for AI coding agents built with Textual, offering a flicker-free and interactive experience compared to existing tools. Toad will be open source, supports any backend language, and uses JSON for communication between frontend and backend.
https://willmcgugan.github.io/announcing-toad/
Will McGugan
Announcing Toad - a universal UI for agentic coding in the terminal
I’m a little salty that neither Anthropic nor Google reached out to me before they released their terminal-based AI coding agents.