DN42 access 本服务为那些无法轻松访问自身网络的用户以及希望体验 dn42 但又不想承担维护自有网络成本的用户提供 dn42 连接 默认情况下，地址从/96地址块中分配，如果您希望租用独立的/96前缀或更大的地址空间，请按照联系方式联系我 所有公开的PoP均已屏蔽来自中国境内的 IP 地址。如果您确实需要dn42 access，请与我联系并提供合理的理由 该服务由AS4242423377提供 - - - - - - - The service provides DN42 connectivity to members who cannot easily access their own networks, as well as to those who would like to explore DN42 without the overhead of maintaining their own network. By default, addresses are allocated from a /96 block. If you wish to lease a dedicated /96 prefix or a larger address space, please contact me using the methods provided in the contact information. All publicly accessible PoP are blocked for IPs originating from within China. DN42 access from within China is not publicly available. If you genuinely require access, please contact me and provide a valid justification. Hosted by AS4242423377. Policy 本服务需要花费时间和金钱才能运行，但为了您的利益，我们免费提供。使用本服务是一种特权，而非权利。您必须合理使用本服务，以确保其他用户也能继续享受同样的便利。任何滥用、误用或干扰服务或其他用户的行为都可能导致您的访问权限立即被暂停或终止。 滥用行为包括但不限于： - 过度使用资源 - 黑客攻击、病毒、木马等，或任何其他可能损害服务或对服务及其用户造成风险的干扰行为 - 传播可能导致民事或刑事责任的不良内容 - - - - - - - This service require real time and financial resources to operate, yet are provided free of charge for your benefit. Access to the services is a privilege, not a right. You must use the services responsibly and considerately to ensure that other users can continue to enjoy the same opportunities. Any misuse, abuse, or activities that disrupt the service or other users may result in immediate suspension or termination of access. Abuse could include, but is not limited to: - Excessive use of resources - Hacking, viruses, trojans etc or any other disruption that could harm or create risk to the services or its users - Distribution of objectional content that could create a civil or criminal liability PoP ## Toronto, Canada Prefix: fdb6:fc6a:e66c:724f:fad1:d2cf::/96 Zerotier: 4753cf475f65b0fb ## Los Angeles, USA coming soon #announcement#service
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@djangoproject · Post #557 · 2018/01/24 05:45
http://go2.anaconda.com/eR0p1W01000NXe0lq4U2f0C Data Scientist-Tested, IT-Approved Operational Best Practices for Enterprise Data Science We know how hard you work to keep things running smoothly at your enterprise. But when it comes to enterprise data science, do you know how to give your data science team the tools they need while also keeping everything secure and stable? #Anaconda
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@djangoproject · Post #506 · 2017/11/26 21:54
Taming the #Python Visualization Jungle It’s no secret that Python has a ton of plotting libraries—but which ones should you use? And how should you go about choosing them? Many people end up sticking with whatever library they first encountered, even if there are now much better tools for the job. Join #Anaconda Co-Founder and CTO Peter Wang and Senior Solutions Architect James Bednar for a live webinar on Wednesday, November 29, at 12pm CT, as they give you some key starting points and demonstrate how to solve a range of common problems. They’ll take a workflow-oriented approach toward exploring the large ecosystem of Python viz libraries, and show you how to: http://bit.ly/2zpATx7
@djangoproject · Post #445 · 2017/09/17 01:01
https://machinelearningmastery.com/setup-python-environment-machine-learning-deep-learning-anaconda/ It can be difficult to install a #Python#machine_learning environment on some platforms. Python itself must be installed first and then there are many packages to install, and it can be confusing for beginners. In this tutorial, you will discover how to set up a Python machine learning development environment using #Anaconda.
@djangoproject · Post #465 · 2017/10/16 08:17
https://goo.gl/ucbkhT #Data_Science for #Big_Data with #Anaconda Enterprise Getting Python and R’s most popular data science libraries to work on a computational cluster can be a major challenge. And in a Big Data world, surmounting this challenge is key to leveraging data science within your organization to make smart, data-driven decisions.
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@djangoproject · Post #526 · 2017/12/19 20:13
https://goo.gl/XT2vGj Anaconda Enterprise 5 new capabilities include: Integrated #data_science experience for the entire organization Collaboration and reproducibility with JupyterLab and #Anaconda Project One-click data science #deployment Scalable architecture for on-premises and cloud deployments
@djangoproject · Post #513 · 2017/11/30 22:00
#AI#Artificial_Intelligence #AJAX #aiohttp #Anaconda #AngularJS #API #Atom #AWS #asyncio (#Asynchronous) #audio #automated_testing #automation #atexit #BeeWare #Big_Data #bitcoin #blockchain #Bluemix #Brython #button #Celery #client #class #classmethod #concurrency #Coroutine #cron #CSS #curl #data_analysis #data_mining #data_processing #database #Deep_Learning#deep_learning #Debian #decorator #deploy #dict #dispatch #django #django_cms #Django_REST_Framework #dropdownbox #Docker #event #Firefox #Flask #form #functions #Generator #GeoDjango #git #Google #GPU #GUI #Gym #host #HTML #httplib #learn #Image_processing #intelligence #input #Instagram #IOT #iPython #Jupyter #lambda #learn #License #Linux #lists #machine_learning #Magenta #map #Matplotlib #Metaprogramming #Micro_services #Micropython #mind #monitoring #MongoDB #modules #Mozilla #Multipart #multi_touch_apps #multiprocessing #Nodes #NoSQL #numeric_computation #numerical #NumPy #network #neural_network #OAuth #object_serialization #OCR #overloading #package #parallel #pipeline #protocols #PostGIS #pyAudioAnalysis #pycon #Pyflakes #PyInstaller #PyPI #PyQt #PySide #PyTorch #pytest #python #Pyvideo_archives #Qt #Raspberry_Pi #React #Redis #random #request #Regular_Expressions (#re) #REST #RSS #satellite #scikit_learn #SciPy #scrapy #searching #selectbox #Selenium #serialization #server #sessions #single_responsibility_principle #socket #Spark #str #submit #task #telegram #template #TensorFlow #test #text_boxes #text #tuples #unicode #Universe #Unix #unit_test #urllib #upload #uWSGI #Web #WSGI
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