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➡️ @DeepLearning_ai
➡️ @MachineLearning_Programming
Step into the future—today! ✨
Explore AI, ML, Data Science, and Computer Vision with us. 🚀
💡 Stay Updated: Latest trends & tutorials.
🌐 Grow Your Network: Engage with experts.
📈 Boost Your Career: Unlock tech mastery.
Subscribe Now!
➡️ @DeepLearning_ai
➡️ @MachineLearning_Programming
Step into the future—today! ✨
❤5
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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
👉 @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.geojsonNeed 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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❤8
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❤3
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
👉 @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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❤10
🤖🧠 MinerU2.5 by Shanghai AI Lab, Peking University & Shanghai Jiao Tong University Sets New Standard for AI-Powered Document Parsing
🗓️ 15 Oct 2025
📚 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 – 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 ...
🗓️ 15 Oct 2025
📚 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 – 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 ...
❤4
Contribute with us to expand the services offered in our channel
We plan to use an advanced AI model to add more information about the most prominent events, models, and articles released and provide explanations.
This requires preparing an infrastructure for our server and purchasing an API for an AI model.
Contribute to the development of our community with us
Contact me @husseinsheikho
We plan to use an advanced AI model to add more information about the most prominent events, models, and articles released and provide explanations.
This requires preparing an infrastructure for our server and purchasing an API for an AI model.
Contribute to the development of our community with us
Contact me @husseinsheikho
❤4