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Source channel @devilsbelow · Post #526 · Feb 9

🌐Weekly News Digest [ February 2 – February 8 ] That was a week when we learned about what Epsteinhad to do with Africa's oil... 💡...and, there were other highlights: 🇦🇴 Angola — Opposition Group Declares Independence of Oil-Rich Enclave of Cabinda from Angola 🇧🇫 Burkina Faso — Burkina Faso Boasts of Record Gold Extraction 🇨🇩 DR Congo — DRC Government Releases Official Response to Rubaya Mine Collapse — US State-Backed Consortium Buys 40% Shares of Two Large Copper-Cobalt Mines From Swiss Company — US Virtus Minerals to Purchase Congolese Copper Producer Chemaf 🇬🇭 Ghana — Private Refinery Makes First Bars From Artisanal Gold Collected by State — French Troops Train Ghanaian Army to Fight Illegal Gold Miners 🇱🇷 Liberia — Ivanhoe Atlantic Appoints Team of US Nationals to Its Board to Facilitate Its Iron Project 🇳🇦 Namibia — Brazil’s Petrobras and France’s TotalEnergies Acquire 85% of Namibia's Oil Field 🇳🇬 Nigeria — Nigeria’s State Oil Corporation Faces Corruption Lawsuit from Local NGO — Nigerians Protest Against Rampimg Up Oil Production In Niger Delta — Nigerian Court Delivers Guilty Verdict Against UK 🇿🇲 Zambia — Delegation From Finland Arrives in Zambia 🌍 Global — US Creates Reserve of Critical Minerals for Civilian Industry #NewsDigest ➡️ Follow to stay informed - @devilsbelow

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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