Question:
What is type hinting in Python, and how does it enhance code quality?
Answer:π @DataScienceQ
What is type hinting in Python, and how does it enhance code quality?
Answer:
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Forwarded from Python | Machine Learning | Coding | R
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Explore AI, ML, Data Science, and Computer Vision with us. π
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Instant geodata visualization from the command line
Now you can interactively view raster and vector layers without launching a desktop GIS or Jupyter.
Just run:
Then visualize data with a single command:
Need to customize the display:
These CLI utilities are based on Leafmap, MapLibre, and LocalTileserver and support all formats compatible with rasterio and geopandas.
See here: https://github.com/opengeos/leafmap
π @codeprogrammer
Now you can interactively view raster and vector layers without launching a desktop GIS or Jupyter.
Just run:
pip install "leafmap[viewer]"
Then visualize data with a single command:
view-raster /path/to/raster.tif
view-vector /path/to/vector.geojson
Need to customize the display:
view-raster /path/to/raster.tif --band 1 --colormap coolwarm
view-vector /path/to/vector.geojson --style liberty
These CLI utilities are based on Leafmap, MapLibre, and LocalTileserver and support all formats compatible with rasterio and geopandas.
See here: https://github.com/opengeos/leafmap
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Free course on learning deep learning concepts
A conceptual and architectural journey through computer vision models in #deeplearning, tracing the evolution from LeNet and AlexNet to ResNet, EfficientNet, and Vision Transformers.
The #course explains the design principles behind skip connections, bottleneck blocks, identity preservation, depth/width trade-offs, and attention.
Each chapter combines clear illustrations, historical context, and side-by-side comparisons to show why architectures look the way they do and how they process information.
Grab it on YouTube
https://youtu.be/tfpGS_doPvY?si=1L_NvEm3Lwpj_Jgl
π @codeprogrammer
A conceptual and architectural journey through computer vision models in #deeplearning, tracing the evolution from LeNet and AlexNet to ResNet, EfficientNet, and Vision Transformers.
The #course explains the design principles behind skip connections, bottleneck blocks, identity preservation, depth/width trade-offs, and attention.
Each chapter combines clear illustrations, historical context, and side-by-side comparisons to show why architectures look the way they do and how they process information.
Grab it on YouTube
https://youtu.be/tfpGS_doPvY?si=1L_NvEm3Lwpj_Jgl
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π€π§ MinerU2.5 by Shanghai AI Lab, Peking University & Shanghai Jiao Tong University Sets New Standard for AI-Powered Document Parsing
ποΈ 15 Oct 2025
π 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 β 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 ...
ποΈ 15 Oct 2025
π 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 β 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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