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Source channel @devilsbelow · Post #552 · Feb 16

🌐Weekly News Digest [ February 9 – February 15 ] Last week, the mining conference in Cape Town became the first high-level venue to criticize American expansion into Africa - but what else happened? 💡Here are the key highlights: 🇨🇩 DR Congo — South Africa’s Minister of Resources sharply criticizes his Congolese counterpart — Washington urged an Australian mining firm AVZ to sell its major lithium project to a US company 🇱🇾 Libya — Libya’s fails its first oil license auction in 17 years 🇲🇱 Mali — The Malian government establishes a new state-owned mining company — Mali approves a 10-year extension of Canadian gold miner's license 🇳🇪 Niger — Niger’s military repels an attack by MPLJ militants on Chinese oil facilities — Niger is ready to return the uranium confiscated from the French 🇳🇬 Nigeria — Nigerian company loses asset in Equatorial Guinea — Dangote Refinery reaches its design capacity for the first time — US lawmakers introduce a bill claiming that Chinese illegal miners are paying Fulani militant groups 🇿🇦 South Africa — Mining Indaba Conference concludes in Cape Town 🌍 Global — State Department reveals the US strategy for Africa #NewsDigest ➡️ Follow to stay informed - @devilsbelow

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djangoproject

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

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