diff --git a/django-under-the-hood-2016/videos/jennifer-akullian-about-mental-health-at-django-under-the-hood-2016.json b/django-under-the-hood-2016/videos/jennifer-akullian-about-mental-health-at-django-under-the-hood-2016.json deleted file mode 100644 index 1a377bb1dd..0000000000 --- a/django-under-the-hood-2016/videos/jennifer-akullian-about-mental-health-at-django-under-the-hood-2016.json +++ /dev/null @@ -1,16 +0,0 @@ -{ - "description": "Slides: https://speakerdeck.com/djangounderthehood/mental-health-keynote-by-jennifer-akullian\n\nDjango: Under The Hood: http://djangounderthehood.com/\n\nDjango: Under The Hood is an annual Django conference for experienced Django developers. Come and learn about the internals of Django, and help to shape its future.", - "language": "eng", - "recorded": "2016-11-03", - "speakers": [ - "Jennifer Akullian" - ], - "thumbnail_url": "https://i.ytimg.com/vi/lzg_IH22CvQ/hqdefault.jpg", - "title": "Jennifer Akullian about Mental Health at Django: Under The Hood 2016", - "videos": [ - { - "type": "youtube", - "url": "https://www.youtube.com/watch?v=lzg_IH22CvQ" - } - ] -} diff --git a/euroscipy-2019/videos/euroscipy-2019-bilbao-understanding-numba-valentin-haenel.json b/euroscipy-2019/videos/euroscipy-2019-bilbao-understanding-numba-valentin-haenel.json deleted file mode 100644 index 28a21251b3..0000000000 --- a/euroscipy-2019/videos/euroscipy-2019-bilbao-understanding-numba-valentin-haenel.json +++ /dev/null @@ -1,17 +0,0 @@ -{ - "description": "| In this talk I will take you on a whirlwind tour of Numba, the\n just-in-time,\n| type-specializing, function compiler for accelerating\n numerically-focused\n| Python. Numba can compile the computationally intensive functions of\n your\n| numerical programs and libraries from Python/NumPy to highly optimized\n binary\n| code. It does this by inferring the data types used inside these\n functions and\n| uses that information to generate code that is specific to those data\n types\n| and specialised for your target hardware. On top of that, it does all\n of this\n| on-the-fly---or just-in-time---as your program runs. This\n significantly reduces\n| the potential complexity that traditionally comes with pre-compiling\n and\n| shipping numerical code for a variety of operating systems, Python\n versions and\n| hardware architectures. All you need in principle, is to\n ``conda install numba``\n| and decorate your compute intensive functions with ``@nuba.jit``!\n\n| This talk will equip you with a mental model of how Numba is\n implemented and\n| how it works at the algorithmic level. You will gain a deeper\n understanding of\n| the types of use-cases where Numba excels and why. Also, you will\n understand\n| the limitations and caveats that exist within Numba, including any\n potential\n| ideas and strategies that might alleviate these. At the end of the\n talk you\n| will be in a good position to decide if Numba is for you and you will\n have\n| learnt about the concrete steps you need to take to include it as a\n dependency\n| in your program or library.\n\nIn this talk I will take you on a whirlwind tour of Numba and you will\nbe quipped with a mental model of how Numba works and what it is good\nat. At the end, you will be able to decide if Numba could be useful for\nyou.\n", - "duration": 1775, - "language": "eng", - "recorded": "2019-09-05", - "speakers": [ - "Valentin Haenel" - ], - "thumbnail_url": "https://i.ytimg.com/vi/WQ1ybsGUkyk/hqdefault.jpg", - "title": "Understanding Numba", - "videos": [ - { - "type": "youtube", - "url": "https://www.youtube.com/watch?v=WQ1ybsGUkyk" - } - ] -} diff --git a/pydata-amsterdam-2019/videos/valentin-haenel-create-cuda-kernels-from-python-using-numba-and-cupy-pydata-amsterdam-2019.json b/pydata-amsterdam-2019/videos/valentin-haenel-create-cuda-kernels-from-python-using-numba-and-cupy-pydata-amsterdam-2019.json deleted file mode 100644 index a061648535..0000000000 --- a/pydata-amsterdam-2019/videos/valentin-haenel-create-cuda-kernels-from-python-using-numba-and-cupy-pydata-amsterdam-2019.json +++ /dev/null @@ -1,17 +0,0 @@ -{ - "description": "We'll explain how to do GPU-Accelerated numerical computing from Python using the Numba Python compiler in combination with the CuPy GPU array library. Numba is an open-source compiler that can translate Python functions for execution on the GPU without requiring users to write any C or C++ code. Numba's just-in-time compilation ability makes it easy to interactively experiment with GPU computing in the Jupyter notebook. Combining Numba with CuPy, a nearly complete implementation of the NumPy API for CUDA, creates a high productivity GPU development environment. Learn the basics of using Numba with CuPy, techniques for automatically parallelizing custom Python functions on arrays, and how to create and launch CUDA kernels entirely from Python. Access to appropriate hardware will be provided in the form of access to GPU based cloud resources.", - "duration": 6369, - "language": "eng", - "recorded": "2019-05-10", - "speakers": [ - "Valentin Haenel" - ], - "thumbnail_url": "https://i.ytimg.com/vi/CQDsT81GyS8/hqdefault.jpg", - "title": "Create CUDA kernels from Python using Numba and CuPy", - "videos": [ - { - "type": "youtube", - "url": "https://www.youtube.com/watch?v=CQDsT81GyS8" - } - ] -} diff --git a/pydata-berlin-2014/videos/abby-a-django-app-to-document-your-ab-tests.json b/pydata-berlin-2014/videos/abby-a-django-app-to-document-your-ab-tests.json index 6eb4f55f7c..4093f3025f 100644 --- a/pydata-berlin-2014/videos/abby-a-django-app-to-document-your-ab-tests.json +++ b/pydata-berlin-2014/videos/abby-a-django-app-to-document-your-ab-tests.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/Vx9UCD6V7y4/hqdefault.jpg", "title": "ABBY: A Django app to document your A/B tests", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20249.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/algorithmic-trading-with-zipline.json b/pydata-berlin-2014/videos/algorithmic-trading-with-zipline.json index 55b2298153..e23f3565e1 100644 --- a/pydata-berlin-2014/videos/algorithmic-trading-with-zipline.json +++ b/pydata-berlin-2014/videos/algorithmic-trading-with-zipline.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/Qva7uxmOZuA/hqdefault.jpg", "title": "Algorithmic Trading with Zipline", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20250.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/building-the-pydata-community.json b/pydata-berlin-2014/videos/building-the-pydata-community.json index f400ac25fc..a5b9b14f45 100644 --- a/pydata-berlin-2014/videos/building-the-pydata-community.json +++ b/pydata-berlin-2014/videos/building-the-pydata-community.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/d9Qm3PPoYNQ/hqdefault.jpg", "title": "Building the PyData Community", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20261.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/commodity-machine-learning.json b/pydata-berlin-2014/videos/commodity-machine-learning.json index 1ed96d5c43..0923990074 100644 --- a/pydata-berlin-2014/videos/commodity-machine-learning.json +++ b/pydata-berlin-2014/videos/commodity-machine-learning.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/kX5jrFqryAE/hqdefault.jpg", "title": "Commodity Machine Learning", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20262.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/conda-a-cross-platform-package-manager-for-any-b-0.json b/pydata-berlin-2014/videos/conda-a-cross-platform-package-manager-for-any-b-0.json index 75f3d94339..67f0ad0005 100644 --- a/pydata-berlin-2014/videos/conda-a-cross-platform-package-manager-for-any-b-0.json +++ b/pydata-berlin-2014/videos/conda-a-cross-platform-package-manager-for-any-b-0.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/o47Nndkwffc/hqdefault.jpg", "title": "Conda: a cross-platform package manager for any binary distribution", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20275.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/data-oriented-programming.json b/pydata-berlin-2014/videos/data-oriented-programming.json index edcf93fa00..a49d6d8449 100644 --- a/pydata-berlin-2014/videos/data-oriented-programming.json +++ b/pydata-berlin-2014/videos/data-oriented-programming.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/KhJSg_rSzj8/hqdefault.jpg", "title": "Data Oriented Programming", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20260.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/dealing-with-complexity.json b/pydata-berlin-2014/videos/dealing-with-complexity.json index 1d48107613..0a58e8c204 100644 --- a/pydata-berlin-2014/videos/dealing-with-complexity.json +++ b/pydata-berlin-2014/videos/dealing-with-complexity.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/1_oU4qW7I9M/hqdefault.jpg", "title": "Dealing With Complexity", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20263.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/driving-moores-law-with-python-powered-machine-l.json b/pydata-berlin-2014/videos/driving-moores-law-with-python-powered-machine-l.json index eb14c6f12e..3faf8998b4 100644 --- a/pydata-berlin-2014/videos/driving-moores-law-with-python-powered-machine-l.json +++ b/pydata-berlin-2014/videos/driving-moores-law-with-python-powered-machine-l.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/Jm-eBD9xR3w/hqdefault.jpg", "title": "Driving Moore's Law with Python-Powered Machine Learning: An Insider's Perspective", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20271.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/exploratory-time-series-analysis-of-nyc-subway-da.json b/pydata-berlin-2014/videos/exploratory-time-series-analysis-of-nyc-subway-da.json index 3d02e327b7..79db15aeeb 100644 --- a/pydata-berlin-2014/videos/exploratory-time-series-analysis-of-nyc-subway-da.json +++ b/pydata-berlin-2014/videos/exploratory-time-series-analysis-of-nyc-subway-da.json @@ -22,10 +22,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/U4p46XdXy6A/hqdefault.jpg", "title": "Exploratory Time Series Analysis of NYC Subway Data", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20270.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/exploring-patent-data-with-python.json b/pydata-berlin-2014/videos/exploring-patent-data-with-python.json index 6a87696c22..27ce3f6cad 100644 --- a/pydata-berlin-2014/videos/exploring-patent-data-with-python.json +++ b/pydata-berlin-2014/videos/exploring-patent-data-with-python.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/LWYiF31jiZ0/hqdefault.jpg", "title": "Exploring Patent Data with Python", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20251.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/extract-transform-load-using-metl.json b/pydata-berlin-2014/videos/extract-transform-load-using-metl.json index dcc76fe747..85fda589d7 100644 --- a/pydata-berlin-2014/videos/extract-transform-load-using-metl.json +++ b/pydata-berlin-2014/videos/extract-transform-load-using-metl.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/NOGXdKbB-gQ/hqdefault.jpg", "title": "Extract Transform Load using mETL", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20253.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/fast-serialization-of-numpy-arrays-with-bloscpack.json b/pydata-berlin-2014/videos/fast-serialization-of-numpy-arrays-with-bloscpack.json deleted file mode 100644 index 08ce2df9d3..0000000000 --- a/pydata-berlin-2014/videos/fast-serialization-of-numpy-arrays-with-bloscpack.json +++ /dev/null @@ -1,38 +0,0 @@ -{ - "alias": "video/3060/fast-serialization-of-numpy-arrays-with-bloscpack", - "category": "PyData Berlin 2014", - "copyright_text": "http://creativecommons.org/licenses/by/3.0/", - "description": "Bloscpack [1] is a reference implementation and file-format for fast\nserialization of numerical data. It features lightweight, chunked and\ncompressed storage, based on the extremely fast Blosc [2] metacodec and\nsupports serialization of Numpy arrays out-of-the-box. Recently, Blosc\n-- being the metacodec that it is -- has received support for using the\npopular and widely used Snappy [3], LZ4 [4], and ZLib [5] codecs, and\nso, now Bloscpack supports serializing Numpy arrays easily with those\ncodecs! In this talk I will present recent benchmarks of Bloscpack\nperformance on a variety of artificial and real-world datasets with a\nspecial focus on the newly available codecs. In these benchmarks I will\ncompare Bloscpack, both performance and usability wise, to alternatives\nsuch as Numpy's native offerings (NPZ and NPY), HDF5/PyTables [6], and\nif time permits, to novel bleeding edge solutions. Lastly I will argue\nthat compressed and chunked storage format such as Bloscpack can be and\nsomewhat already is a useful substrate on which to build more powerful\napplications such as online analytical processing engines and\ndistributed computing frameworks. [1]:\nhttps://github.com/Blosc/bloscpack [2]:\nhttps://github.com/Blosc/c-blosc/ [3]: http://code.google.com/p/snappy/\n[4]: http://code.google.com/p/lz4/ [5]: http://www.zlib.net/ [6]:\nhttp://www.pytables.org/moin\n", - "duration": null, - "id": 3060, - "language": "eng", - "quality_notes": "", - "recorded": "2014-07-27", - "related_urls": [ - "http://code.google.com/p/lz4/", - "http://code.google.com/p/snappy/", - "http://www.pytables.org/moin", - "http://www.zlib.net/", - "https://github.com/Blosc/bloscpack", - "https://github.com/Blosc/c-blosc/" - ], - "slug": "fast-serialization-of-numpy-arrays-with-bloscpack", - "speakers": [ - "Valentin Haenel" - ], - "summary": "", - "tags": [], - "thumbnail_url": "https://i.ytimg.com/vi/TZdqeEd7iTM/hqdefault.jpg", - "title": "Fast Serialization of Numpy Arrays with Bloscpack", - "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20226.mp4" - }, - { - "length": 0, - "type": "youtube", - "url": "https://www.youtube.com/watch?v=TZdqeEd7iTM" - } - ] -} diff --git a/pydata-berlin-2014/videos/faster-than-google-optimization-lessons-in-pytho.json b/pydata-berlin-2014/videos/faster-than-google-optimization-lessons-in-pytho.json index 9e4be4d056..93e7c7a721 100644 --- a/pydata-berlin-2014/videos/faster-than-google-optimization-lessons-in-pytho.json +++ b/pydata-berlin-2014/videos/faster-than-google-optimization-lessons-in-pytho.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/vU4TlwZzTfU/hqdefault.jpg", "title": "Faster than Google? Optimization lessons in Python.", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20228.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/generators-will-free-your-mind.json b/pydata-berlin-2014/videos/generators-will-free-your-mind.json index 857eda3464..de64f3e83f 100644 --- a/pydata-berlin-2014/videos/generators-will-free-your-mind.json +++ b/pydata-berlin-2014/videos/generators-will-free-your-mind.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/JasPrZqImxo/hqdefault.jpg", "title": "Generators Will Free Your Mind", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20258.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/honza-kral-make-sense-of-your-big-data-using.json b/pydata-berlin-2014/videos/honza-kral-make-sense-of-your-big-data-using.json index 624dd46f12..8854566114 100644 --- a/pydata-berlin-2014/videos/honza-kral-make-sense-of-your-big-data-using.json +++ b/pydata-berlin-2014/videos/honza-kral-make-sense-of-your-big-data-using.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/sCktucuv5Yo/hqdefault.jpg", "title": "Make sense of your (big) data using Elasticsearch", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20235.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/how-to-spy-with-python.json b/pydata-berlin-2014/videos/how-to-spy-with-python.json index cd4412243d..08de8409fa 100644 --- a/pydata-berlin-2014/videos/how-to-spy-with-python.json +++ b/pydata-berlin-2014/videos/how-to-spy-with-python.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/8m3fFPCUPQg/hqdefault.jpg", "title": "How to Spy with Python", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20274.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/interactive-analysis-of-large-financial-data-se.json b/pydata-berlin-2014/videos/interactive-analysis-of-large-financial-data-se.json index 07ef0454c5..a0596ff8ea 100644 --- a/pydata-berlin-2014/videos/interactive-analysis-of-large-financial-data-se.json +++ b/pydata-berlin-2014/videos/interactive-analysis-of-large-financial-data-se.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/XyqlduIcc2g/hqdefault.jpg", "title": "Interactive Analysis of (Large) Financial Data Sets", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20259.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/intro-to-convnets.json b/pydata-berlin-2014/videos/intro-to-convnets.json index 8edd7733b8..b7a2d08617 100644 --- a/pydata-berlin-2014/videos/intro-to-convnets.json +++ b/pydata-berlin-2014/videos/intro-to-convnets.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/W9_SNGymRwo/hqdefault.jpg", "title": "Intro to ConvNets", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20257.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/introduction-to-the-signal-processing-and-classif.json b/pydata-berlin-2014/videos/introduction-to-the-signal-processing-and-classif.json index aba04e9af7..1cedd58963 100644 --- a/pydata-berlin-2014/videos/introduction-to-the-signal-processing-and-classif.json +++ b/pydata-berlin-2014/videos/introduction-to-the-signal-processing-and-classif.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/KobSyPceR6I/hqdefault.jpg", "title": "Introduction to the Signal Processing and Classification Environment pySPACE", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20268.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/ipython-and-sympy-to-develop-a-kalman-filter-for.json b/pydata-berlin-2014/videos/ipython-and-sympy-to-develop-a-kalman-filter-for.json index 0917a23ea9..06a6dfe8a6 100644 --- a/pydata-berlin-2014/videos/ipython-and-sympy-to-develop-a-kalman-filter-for.json +++ b/pydata-berlin-2014/videos/ipython-and-sympy-to-develop-a-kalman-filter-for.json @@ -20,10 +20,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/XSRr2HHedrY/hqdefault.jpg", "title": "IPython and Sympy to Develop a Kalman Filter for Multisensor Data Fusion", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20238.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/lightning-talks-7.json b/pydata-berlin-2014/videos/lightning-talks-7.json index 938622bda1..8564b486ca 100644 --- a/pydata-berlin-2014/videos/lightning-talks-7.json +++ b/pydata-berlin-2014/videos/lightning-talks-7.json @@ -18,10 +18,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/C_GBFxt_3s0/hqdefault.jpg", "title": "Lightning Talks", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/29242.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/low-rank-matrix-approximations-in-python.json b/pydata-berlin-2014/videos/low-rank-matrix-approximations-in-python.json index 4863d5606d..eccf246adf 100644 --- a/pydata-berlin-2014/videos/low-rank-matrix-approximations-in-python.json +++ b/pydata-berlin-2014/videos/low-rank-matrix-approximations-in-python.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/kfEWZA-b-YQ/hqdefault.jpg", "title": "Low-rank matrix approximations in Python", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20266.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/massively-parallel-processing-with-procedural-pyt.json b/pydata-berlin-2014/videos/massively-parallel-processing-with-procedural-pyt.json index 6fec61a87f..a3b038f18f 100644 --- a/pydata-berlin-2014/videos/massively-parallel-processing-with-procedural-pyt.json +++ b/pydata-berlin-2014/videos/massively-parallel-processing-with-procedural-pyt.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/rv6J6CYbGy4/hqdefault.jpg", "title": "Massively Parallel Processing with Procedural Python", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20232.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/packaging-and-deployment.json b/pydata-berlin-2014/videos/packaging-and-deployment.json index 9fe39648fc..3759a9685a 100644 --- a/pydata-berlin-2014/videos/packaging-and-deployment.json +++ b/pydata-berlin-2014/videos/packaging-and-deployment.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/bR_WGj5MOlY/hqdefault.jpg", "title": "Packaging and Deployment", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20276.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/pandas-thumb-unexpected-evolutionary-use-of-a-p.json b/pydata-berlin-2014/videos/pandas-thumb-unexpected-evolutionary-use-of-a-p.json index 4f31b6e05d..511ac39b31 100644 --- a/pydata-berlin-2014/videos/pandas-thumb-unexpected-evolutionary-use-of-a-p.json +++ b/pydata-berlin-2014/videos/pandas-thumb-unexpected-evolutionary-use-of-a-p.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/CNQ_Ib4yxgQ/hqdefault.jpg", "title": "Pandas' Thumb: unexpected evolutionary use of a Python library.", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20240.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/panel-the-challenges-and-frontiers-of-data-scien.json b/pydata-berlin-2014/videos/panel-the-challenges-and-frontiers-of-data-scien.json index bd128c0433..00f684fc08 100644 --- a/pydata-berlin-2014/videos/panel-the-challenges-and-frontiers-of-data-scien.json +++ b/pydata-berlin-2014/videos/panel-the-challenges-and-frontiers-of-data-scien.json @@ -13,18 +13,13 @@ "Adam Drake", "Ian Ozswald", "James Powell", - "Kim Nilsoon", - "Valentin Haenel" + "Kim Nilsoon" ], "summary": "", "tags": [], "thumbnail_url": "https://i.ytimg.com/vi/AtkDHrzgs7c/hqdefault.jpg", "title": "Panel: The challenges and frontiers of data science in Europe", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/29257.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/parallel-processing-using-python-and-gearman.json b/pydata-berlin-2014/videos/parallel-processing-using-python-and-gearman.json index e0e277bfed..ee5cf6eba1 100644 --- a/pydata-berlin-2014/videos/parallel-processing-using-python-and-gearman.json +++ b/pydata-berlin-2014/videos/parallel-processing-using-python-and-gearman.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/FRnP4UIgRI4/hqdefault.jpg", "title": "Parallel processing using python and gearman", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20234.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/python-and-pandas-as-back-end-to-real-time-data-d.json b/pydata-berlin-2014/videos/python-and-pandas-as-back-end-to-real-time-data-d.json index 8beb126457..da729cbb7e 100644 --- a/pydata-berlin-2014/videos/python-and-pandas-as-back-end-to-real-time-data-d.json +++ b/pydata-berlin-2014/videos/python-and-pandas-as-back-end-to-real-time-data-d.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/I8xBoXgJ5RM/hqdefault.jpg", "title": "Python and pandas as back end to real-time data driven applications", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20246.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/quantified-self-analyzing-the-big-data-of-our-da.json b/pydata-berlin-2014/videos/quantified-self-analyzing-the-big-data-of-our-da.json index 7163e96761..0fc06113ce 100644 --- a/pydata-berlin-2014/videos/quantified-self-analyzing-the-big-data-of-our-da.json +++ b/pydata-berlin-2014/videos/quantified-self-analyzing-the-big-data-of-our-da.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/tSyQ36Zbkc0/hqdefault.jpg", "title": "Quantified Self: Analyzing the Big Data of our Daily Life", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20231.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/semantic-python-mastering-linked-data-with-pytho.json b/pydata-berlin-2014/videos/semantic-python-mastering-linked-data-with-pytho.json index 9b678d0ba9..9aba783591 100644 --- a/pydata-berlin-2014/videos/semantic-python-mastering-linked-data-with-pytho.json +++ b/pydata-berlin-2014/videos/semantic-python-mastering-linked-data-with-pytho.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/5DCS9LE-8rE/hqdefault.jpg", "title": "Semantic Python: Mastering Linked Data with Python", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20244.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/speed-without-drag.json b/pydata-berlin-2014/videos/speed-without-drag.json index 410e442796..2c615973f2 100644 --- a/pydata-berlin-2014/videos/speed-without-drag.json +++ b/pydata-berlin-2014/videos/speed-without-drag.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/cRb96NEHW4I/hqdefault.jpg", "title": "Speed Without Drag", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20256.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/street-fighting-trend-research.json b/pydata-berlin-2014/videos/street-fighting-trend-research.json index 04218b3aa3..138429a7fb 100644 --- a/pydata-berlin-2014/videos/street-fighting-trend-research.json +++ b/pydata-berlin-2014/videos/street-fighting-trend-research.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/4c_AmPWo-iw/hqdefault.jpg", "title": "Street Fighting Trend Research", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20237.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2014/videos/visualising-data-through-pandas.json b/pydata-berlin-2014/videos/visualising-data-through-pandas.json index 154efece33..86a0115ed6 100644 --- a/pydata-berlin-2014/videos/visualising-data-through-pandas.json +++ b/pydata-berlin-2014/videos/visualising-data-through-pandas.json @@ -17,10 +17,6 @@ "thumbnail_url": "https://i.ytimg.com/vi/ZW8Aei2wlsM/hqdefault.jpg", "title": "Visualising Data through Pandas", "videos": [ - { - "type": "mp4", - "url": "http://video.ep14.c3voc.de/20269.mp4" - }, { "length": 0, "type": "youtube", diff --git a/pydata-berlin-2018/videos/battle-hardened-advice-on-efficient-data-loading-for-deep-learning-on-videos-valentin-haenel.json b/pydata-berlin-2018/videos/battle-hardened-advice-on-efficient-data-loading-for-deep-learning-on-videos-valentin-haenel.json deleted file mode 100644 index 49ef467cd4..0000000000 --- a/pydata-berlin-2018/videos/battle-hardened-advice-on-efficient-data-loading-for-deep-learning-on-videos-valentin-haenel.json +++ /dev/null @@ -1,26 +0,0 @@ -{ - "abstract": "Getting GPUs fully utilized can be tricky when dealing with video data.\nIn this talk I will explore this topic in depth and present some\ninsights gained during a year of Deep Learning on videos at TwentyBN.\nSpecifically, the problem is that such data may no longer fit into\nsystem-memory and we had to devise some efficient loading and decoding\nschemes to load data as quickly as possible. The talk will feature set\nof best practices and some open source recommendations that can help\naccelerate your deep learning process on video problems in practice.\nImportantly, I will discuss various options and ideas for data storage,\nincluding our own open source video and image format: GulpIO. I will\ndiscuss the effect that a good video codec has and how various codecs\ncompare to each other. Also, I will explain how to properly benchmark\nprograms that read from disc using a tool called ``nocache``. Finally, I\nwill present a set of benchmarks on real-world data under real-world\nconditions.\n", - "copyright_text": null, - "description": "Getting GPUs fully utilized can be tricky when dealing with video data.\nIn this talk I will explore this topic in depth and present some\ninsights gained during a year of Deep Learning on videos at TwentyBN.\nThe talk will feature set of best practices and some open source\nrecommendations that can help accelerate your deep learning process on\nvideo problems in practice.\n", - "duration": 1958, - "language": "eng", - "recorded": "2018-07-08", - "related_urls": [ - { - "label": "Conference schedule", - "url": "https://pydata.org/berlin2018/schedule/" - } - ], - "speakers": [ - "Valentin Haenel" - ], - "tags": [], - "thumbnail_url": "https://i.ytimg.com/vi/wtcvD3RQt3c/maxresdefault.jpg", - "title": "Battle-hardened advice on efficient data loading for deep learning on videos.", - "videos": [ - { - "type": "youtube", - "url": "https://www.youtube.com/watch?v=wtcvD3RQt3c" - } - ] -}