41–50 of 76 posts
Been using Tensorflow embedded in a mobile app for a few months and honestly, I’m constantly surprised at how well thought-out the tooling is, and how quickly you can get results. Conversely, I think a few things are still unnecessarily dense (installing dependencies, optimizing hyper-parameters, and some of the embedded/XLA stuff is very raw). Kudos to the team though. It sounds like they’re on the right track with…
How do I get started with machine learning? I have a couple of applications in mind, mostly time series predictions. But the machine learning field seems to be vast and I don't know where to start.
Deep learning is primarily a study of multi-layered neural networks, spanning over a great range of model architectures. This course is taught in the MSc program in Artificial Intelligence of the University of Amsterdam. In this course we study the theory of deep learning, namely of modern, multi-layered neural networks trained on big data. The course focuses particularly on computer vision and language modelling, which are perhaps two of the most recognizable and impressive applications of the deep learning theory.
Been using Tensorflow embedded in a mobile app for a few months and honestly, I’m constantly surprised at how well thought-out the tooling is, and how quickly you can get results. Conversely, I think a few things are still unnecessarily dense (installing dependencies, optimizing hyper-parameters, and some of the embedded/XLA stuff is very raw). Kudos to the team though. It sounds like they’re on the right track with…
How do you embed in a mobile app?
The new, still experimental way is to compile your neural net into executable code with their XLA / tfcompile tool, and link that into your app. They are adding more docs on this on the TensorFlow website [1].
[0]: https://github.com/tensorflow/tensorflow/tree/master/tensorf...
[1]: https://www.tensorflow.org/versions/master/experimental/xla/...
Kudos to the team. Anybody know if we can we train in languages other than Python yet (or do I have that wrong)?
I'll discuss this a bit during my talk at the dev summit. The short answer is no. The long answer is yes, but only if you create the model in Python, export it, and then feed training data in other languages. There are some people doing exactly that. Long term, I'd like to give all languages equal footing, but there's quite a bit of work left.
Does Python have intrinsic qualities that other languages don't possess or is it that the huge initial investment in creating TensorFlow was based on Python and duplicating that effort somewhere else would require too much work?
For anyone updating to 1.0-- There are quite a few breaking changes but there is a very helpful conversion script here: https://github.com/tensorflow/tensorflow/tree/r1.0/tensorflo... . You can find the breaking changes in the 1.0 release here: https://github.com/tensorflow/tensorflow/releases/tag/v1.0.0
Amazing work; it makes using AI and Deep Learning accessible for everyone here really. If you haven't seen it check this out for an intro: https://www.youtube.com/watch?v=vq2nnJ4g6N0 I wish AMD graphics cards were supported fully. I really think AMD should find a way to work with the Tensor Flow team on this...