#MXNet #Scala package is out! http://goo.gl/bUClIN Thanks to everyone's efforts! @javelinjs @tqchenml @yanqingmen Happy using! #DMLC
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HIRING: Machine Learning Engineer, Web Ads and Open-loop E-Commerce -USDS / Mountain View
USD 228K+
ai-jobs.netMachine Learning Engineer, Web Ads and Open-loop E-Commerce -USDS at TikTok - Mountain ViewTikTok is hiring for Full Time Machine Learning Engineer, Web Ads and Open-loop E-Commerce -USDS - Mountain View, a senior-level AI/ML/Data Science role offering benefits such as 401(k) matching, career development, equity / stock options, flex hours, flexible spending account, flex vacation, health care, insurance, medical leave, parental leave, transparency, travel.
Note to self: #NVIDIA have an open-source inference server for machine learning models. (They mostly sell SaaS on top of it)
Supports #TensorFlow, #PyTorch, #ONNX, #TensorRT, #mxnet.
Runs on #k8s. Features queue control, monitoring.
Triton Inference Server https://github.com/triton-inference-server
GitHubTriton Inference ServerTriton Inference Server has 33 repositories available. Follow their code on GitHub.
MXNet doesn't look difficult...but I see two mayor issues:
a) Community yet small
b) Lack of pretrained models for transfer learning. A big hit would be support by Hugginface models and pretrained models with ImageNet.
(1/n)𝐍𝐞𝐰 𝐫𝐞𝐥𝐞𝐚𝐬𝐞 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐃𝐢𝐯𝐞 𝐢𝐧𝐭𝐨 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐛𝐨𝐨𝐤! 
The 𝐃𝐢𝐯𝐞 𝐢𝐧𝐭𝐨 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 book is an educational project by Amazon's scientists and other contributors focusing on deep learning models and their applications. It is interactive and available online for 𝐟𝐫𝐞𝐞 and implemented with multiple deep learning frameworks such as 𝐏𝐲𝐓𝐨𝐫𝐜𝐡, 𝐍𝐮𝐦𝐏𝐲/𝐌𝐗𝐍𝐞𝐭, 𝐆𝐨𝐨𝐠𝐥𝐞 𝐉𝐀𝐗, and 𝐓𝐞𝐧𝐬𝐨𝐫𝐅𝐥𝐨𝐰 
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If someone here can give me an explanation for "why #mxnet is not more widely used while #Tensorflow and #Pytorch are slower?". I like TF and PT but mxnet is IMHO not used enough.