Training a Deep Learning Model for Echogram Semantic Segmentation
In this tutorial we build a deep-learning pipeline for echogram segmentation using open-source tools. Echograms are two-dimensional plots of acoustic echo intensity versus time and depth recorded using sonar instruments, in our case echosounders.
https://oceanstream.io/training-a-deep-learning-model-for-echogram-semantic-segmentation/
In this tutorial we build a deep-learning pipeline for echogram segmentation using open-source tools. Echograms are two-dimensional plots of acoustic echo intensity versus time and depth recorded using sonar instruments, in our case echosounders.
https://oceanstream.io/training-a-deep-learning-model-for-echogram-semantic-segmentation/
OceanStream
Training a Deep Learning Model for Echogram Semantic Segmentation
In this tutorial we build a deep‑learning pipeline for echogram segmentation using open‑source tools. Echograms are two‑dimensional plots of acoustic echo intensity versus time and depth recorded using sonar instruments, in our case echosounders.
Python 3.14 Is Here. How Fast Is It?
Python 3.14 delivers notable performance improvements, including up to 27% speedup in some benchmarks compared to Python 3.13, and enhanced free-threaded execution for better multithreading. The new release also adds features like syntax highlighting in the REPL and improved concurrency support.
https://blog.miguelgrinberg.com/post/python-3-14-is-here-how-fast-is-it
Python 3.14 delivers notable performance improvements, including up to 27% speedup in some benchmarks compared to Python 3.13, and enhanced free-threaded execution for better multithreading. The new release also adds features like syntax highlighting in the REPL and improved concurrency support.
https://blog.miguelgrinberg.com/post/python-3-14-is-here-how-fast-is-it
Miguelgrinberg
Python 3.14 Is Here. How Fast Is It?
In November of 2024 I wrote a blog post titled "Is Python Really That Slow?", in which I tested several versions of Python and noted the steady progress the language has been making in terms of…
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How to Level Up Your Python Logs with Structlog
This Structlog guide covers configuration context JSON output error handling and OpenTelemetry integration to make your logs a useful signal for Observability.
https://www.dash0.com/guides/python-logging-with-structlog
This Structlog guide covers configuration context JSON output error handling and OpenTelemetry integration to make your logs a useful signal for Observability.
https://www.dash0.com/guides/python-logging-with-structlog
Dash0
How to Level Up Your Python Logs with Structlog · Dash0
This Structlog guide covers configuration context JSON output error handling and OpenTelemetry integration to make your logs a useful signal for Observability
PyTorch 2.9
PyTorch 2.9 introduces new features including a stable libtorch ABI for C++/CUDA extensions, symmetric memory programming for easy multi-GPU kernel development, and enhanced control over graph break handling in torch.compile. It expands wheel support for AMD ROCm, Intel XPU, and CUDA 13, adds FlexAttention optimizations on Intel GPUs and X86 CPUs, and improves Arm platform performance wi...
https://pytorch.org/blog/pytorch-2-9/
PyTorch 2.9 introduces new features including a stable libtorch ABI for C++/CUDA extensions, symmetric memory programming for easy multi-GPU kernel development, and enhanced control over graph break handling in torch.compile. It expands wheel support for AMD ROCm, Intel XPU, and CUDA 13, adds FlexAttention optimizations on Intel GPUs and X86 CPUs, and improves Arm platform performance wi...
https://pytorch.org/blog/pytorch-2-9/
Neural Networks: Simpler Than You Think
The post presents a straightforward implementation of a neural network from scratch in Python, explaining core concepts such as neurons, layers, weights, biases, activation functions, and training through backpropagation. It demonstrates building and training a simple neural network to approximate a sine wave, highlighting that despite its simplicity, the network can learn complex patter...
https://www.hamza.se/blog/neural-networks
The post presents a straightforward implementation of a neural network from scratch in Python, explaining core concepts such as neurons, layers, weights, biases, activation functions, and training through backpropagation. It demonstrates building and training a simple neural network to approximate a sine wave, highlighting that despite its simplicity, the network can learn complex patter...
https://www.hamza.se/blog/neural-networks
Hamza's Portfolio & Blog
Neural Networks: Simpler Than You Think | Hamza's Blog
A walkthrough of implementing a neural network from scratch in Python, exploring what makes these seemingly complex systems actually quite straightforward.
rightnow-cli
Claude Code for CUDA. Free AI assistant that actually understands GPU architecture.
https://github.com/RightNow-AI/rightnow-cli
Claude Code for CUDA. Free AI assistant that actually understands GPU architecture.
https://github.com/RightNow-AI/rightnow-cli
GitHub
GitHub - RightNow-AI/rightnow-cli: Claude Code for CUDA. Free AI assistant that actually understands GPU architecture
Claude Code for CUDA. Free AI assistant that actually understands GPU architecture - RightNow-AI/rightnow-cli
Buridan UI
Beautifully designed Reflex components to build your web apps faster. Open source.
https://github.com/buridan-ui/ui
Beautifully designed Reflex components to build your web apps faster. Open source.
https://github.com/buridan-ui/ui
GitHub
GitHub - buridan-ui/ui: Composable, themeable components designed for Reflex. Extend, override, and ship without fighting the framework.…
Composable, themeable components designed for Reflex. Extend, override, and ship without fighting the framework. Open source. - buridan-ui/ui
Handy Python REPL Modifications
The article describes custom modifications to the Python REPL to make it behave more like a favorite editor, including adding new keyboard shortcuts for code navigation, editing, and inserting example data structures. These changes, enabled through a PYTHONSTARTUP file and packaged in a library called pyrepl-hacks, enhance productivity by allowing quicker code writing and editing with si...
https://treyhunner.com/2025/10/handy-python-repl-modifications/
The article describes custom modifications to the Python REPL to make it behave more like a favorite editor, including adding new keyboard shortcuts for code navigation, editing, and inserting example data structures. These changes, enabled through a PYTHONSTARTUP file and packaged in a library called pyrepl-hacks, enhance productivity by allowing quicker code writing and editing with si...
https://treyhunner.com/2025/10/handy-python-repl-modifications/
Treyhunner
Handy Python REPL Modifications
I find myself in the Python REPL a lot. I open up the REPL to play with an idea, to use Python as a calculator or quick and dirty text parsing tool, …
TorchCurves - differentiable parametric curves in PyTorch
PyTorch parametric curves spanned by B-Splines or Legendre polynomials for KANs, Embeddings, or PDE solvers.
https://github.com/alexshtf/torchcurves
PyTorch parametric curves spanned by B-Splines or Legendre polynomials for KANs, Embeddings, or PDE solvers.
https://github.com/alexshtf/torchcurves
GitHub
GitHub - alexshtf/torchcurves: Parametric differentiable curves with PyTorch for KANs, continuous embeddings, or shape-restricted…
Parametric differentiable curves with PyTorch for KANs, continuous embeddings, or shape-restricted models - alexshtf/torchcurves
Killing the GIL: How To Use Python 3.14's Free-Threading Upgrade
The global interpreter lock (GIL) has been interfering with true parallelism in Python. That ends with Python 3.14.
https://www.neelsomaniblog.com/p/killing-the-gil-how-to-use-python
The global interpreter lock (GIL) has been interfering with true parallelism in Python. That ends with Python 3.14.
https://www.neelsomaniblog.com/p/killing-the-gil-how-to-use-python
Neelsomaniblog
Killing the GIL: How To Use Python 3.14's Free-Threading Upgrade
The global interpreter lock (GIL) has been interfering with true parallelism in Python. That ends with Python 3.14.
EdgeAI for Beginners
This course is designed to guide beginners through the exciting world of Edge AI, covering fundamental concepts, popular models, inference techniques, device-specific applications, model optimization, and the development of intelligent Edge AI agents.
https://github.com/microsoft/edgeai-for-beginners
This course is designed to guide beginners through the exciting world of Edge AI, covering fundamental concepts, popular models, inference techniques, device-specific applications, model optimization, and the development of intelligent Edge AI agents.
https://github.com/microsoft/edgeai-for-beginners
GitHub
GitHub - microsoft/edgeai-for-beginners: This course is designed to guide beginners through the exciting world of Edge AI, covering…
This course is designed to guide beginners through the exciting world of Edge AI, covering fundamental concepts, popular models, inference techniques, device-specific applications, model optimizati...