wannaphongTensorBoard is the best visualization for training model. It can working offline. Most clusters aren't have online access.
HabrКонвейер машинного обучения для классификации рукописных цифр MNIST с использованием TensorFlow Extended (TFX)
В рамках данной статьи будет рассмотрено построение конвейера машинного обучения для классификации рукописных цифр из базы данных MNIST с использованием фреймворка TensorFlow и TFX, а также мониторинг процесса обучения с помощью TensorBoard и выпуск модели с автоматической генерацией к ней API с помощью TensorFlow Model Server. Основная цель данной статьи заключается в восполнении информационного пробела по теме использования TFX в контексте решения задачи классификации рукописных цифр MNIST, которая уже была представлена TensorFlow в виде одноименного репозитория tfx/tfx/examples/mnist .
https://habr.com/ru/articles/898140/
#python #tensorflow #machine_learning #конвейеры #tfx #tensorflowmodelserver #tensorboard
Конвейер машинного обучения для классификации рукописных цифр MNIST с использованием TensorFlow Extended (TFX)
В рамках данной статьи будет рассмотрено построение конвейера машинного обучения для классификации рукописных цифр из базы данных MNIST с использованием фреймворка TensorFlow и TFX, а также мониторинг...
ViraptorOnce you dig deep enough, there's something really addictive/exciting about seeing the loss curve dipping lower than the last time.
Give me your tasty predictions, machine!
#ml #tensorboard
Give me your tasty predictions, machine!
#ml #tensorboard
Niklas HeidloffOn my blog: Training Models locally via Containers
#Tensorboard #FineTuning #LLM #AI
https://heidloff.net/article/training-models-locally-containers-tensorboard/
NirroI was surprised to learn that you cannot do ROC curves on #tensorboard directly... but after banging my head against the keyboard, I've found that you can send #matplotlib grahps to it.
(And also torchmetrics gives you nice matplotlib graphs for your metrics.)
Kito D. MannRT @stackdpodcast: @dhinojosa and @kito99 @frankgreco and @zsevarac. Visual Recognition ML API for #Java, #DeepNets, #LLMs, Stack #OverflowAI, #StableDiffusion, #ChatGPT, #OpenJDK Panama, #Llma 2, #PromptEngineering, #ApacheZeppelin, #Tensorboard, #H2O.ai, #Spark, and more! https://www.pubhouse.net/2023/10/stackd-67-ai-nullpointers.html
RT @stackdpodcast: #67: @dhinojosa and @kito99 dive into #ai with fellow @Java_Champions @frankgreco and @zsevarac: Visual Recognition ML API for Java, #DeepNets, #StableDiffusion, #ChatGPT, #OpenJDK Panama, #Llma 2, #PromptEngineering, #ApacheZeppelin, #Tensorboard, #H2O.ai, #Spark, and more! https://www.pubhouse.net/2023/10/stackd-67-ai-nullpointers.html
maxyNew optimization run in progress!
Will the new run, with more hidden neurons, more stupid bugs, be able to over-take the old one?
Find out tomorrow, I guess. Or wait, let's just check once more... #tensorboard addiction.
Kunal BhallaHello, world!
I'm currently working on #tools for #ML engineers at #Meta [#mlops, #pytorch, #tensorboard, #debugging], tend to write for developers at explog.in [#devtools, #python] and spend way too much time configuring #emacs. Past lives have involved #android, #maps and #reliability.
[wow, edits; so many hashtags] #introduction
Johnson Suntbparse: Load tensorboard event logs as pandas DataFrames for scientific plotting
- Supports parsing tensorboard event scalars, tensors, histograms, images, audio, hparams, and text.
- Supports event generated by PyTorch, Tensorboard/Keras, and TensorboardX.
- Allows parsing multiple tensorboard event files in a hierarchical directory structure.
https://github.com/j3soon/tbparse
#Python #TensorBoard #Pandas #PyTorch #TensorFlow #MachineLearning #DeepLearning #DataScience
GitHub - j3soon/tbparse: Load tensorboard event logs as pandas DataFrames for scientific plotting; Supports both PyTorch and TensorFlow
Load tensorboard event logs as pandas DataFrames for scientific plotting; Supports both PyTorch and TensorFlow - GitHub - j3soon/tbparse: Load tensorboard event logs as pandas DataFrames for scient...