Complete code examples for Machine Translation with Attention, Image Captioning, Text Generation, and DCGAN implemented with tf.keras and eager execution

“Complete code examples for Machine Translation with Attention, Image Captioning, Text Generation…” https://medium.com/tensorflow/complete-code-examples-for-machine-translation-with-attention-image-captioning-text-generation-51663d07a63d

#tensorflow #tutorial

Fast image-to-image translation in the browser. With 3 trained models introduced. Plus a processed dataset of 1000 images for edges2cats translation.

Demo: https://zaidalyafeai.github.io/pix2pix/cats.html
Code: https://github.com/zaidalyafeai/zaidalyafeai.github.io/tree/master/pix2pix

#tf #tensorflow #tfjs #pix2pix #cv

Plug-and-play differential privacy for your tensorflow code

#GoogleAI has just released a new library for training machine learning models with (differential) privacy for training data.

where you would write tf.train.GradientDescentOptimizer
instead just swap in the DPGradientDescentOptimizer


Tutorial: https://github.com/tensorflow/privacy/blob/master/tutorials/mnist_dpsgd_tutorial.py
Link: https://github.com/tensorflow/privacy

#Privacy #tensorflow

Use Machine Learning to filter messages in the browser

Article on filtering messages during #Twitch streaming with #tensorflow.

Link: https://dev.to/embiem/use-machine-learning-to-filter-messages-in-the-browser-4i19

#DL #NN #NLP #tensorflowjs

Using Nucleus and TensorFlow for DNA Sequencing Error Correction

This is a new #tutorial of the Genomics team in #GoogleBrain. Good place to start with #deeplearning for #genomics using Nucleus and #Tensorflow.

Link: https://medium.com/tensorflow/using-nucleus-and-tensorflow-for-dna-sequencing-error-correction-47f3f7fc1a50
Google colab: https://colab.research.google.com/github/google/nucleus/blob/master/nucleus/examples/dna_sequencing_error_correction.ipynb

#Google #healthcare

Lingvo: A TensorFlow Framework for Sequence Modeling

Release from #GoogleAI: general #tensorflow framework for #NLP.

#Lingvo is a deep learning framework used for sequence modeling tasks like machine translation, speech recognition, and speech synthesis.

Link: https://medium.com/tensorflow/lingvo-a-tensorflow-framework-for-sequence-modeling-8b1d6ffba5bb
Github: https://github.com/tensorflow/lingvo

Small $ 60 camera for #CV tasks

JeVois — video sensor + quad-core CPU + USB video + serial port, all in a tiny, self-contained package size of a small coin.


YouTube: https://www.youtube.com/watch?v=7cTfOckkGlE
Project site: http://jevois.org
Link for shop: https://www.jevoisinc.com


#deeplearning #hardware #tensorflow

Filter autoselect in VSCO by Google

#VSCO used #TensorFlow Lite to develop the 'For This Photo' feature, which uses on-device ML to suggest photo filter presets from a curated list.

YouTube: https://www.youtube.com/watch?v=fHbjfeitIvE
Link: https://medium.com/tensorflow/suggesting-presets-for-images-building-for-this-photo-at-vsco-9b94041c4ba4

#mobile #device #cv #dl

​​The new ResNet PoseNet model is much more accurate than the MobileNet one (the trade off being size & speed). The model is quantized & 25MB.
Pose estimation model, capable of running on devices

This model is really great for art installations or running on desktops.

Demo (requires camera, will work on desktop): https://storage.googleapis.com/tfjs-models/demos/posenet/camera.html?linkId=69346544
Github: https://github.com/tensorflow/tfjs-models/tree/master/posenet

#tensorflow #tensorflowjs #js #pose #poseestimation #posenet #ResNet #device #ondevice

​​Photo to anime portrait

U-GAT-IT — Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation.

Link: https://github.com/taki0112/UGATIT

#Tensorflow #GAN #CV #DL #anime

Great collections of Data Science learning materials

The list includes free books and online courses on range of DS-related disciplines:

Machine learning (#ML)
Deep Learning (#DL)
Reinforcement learning (#RL)
#NLP

Tutorials on #Keras, #Tensorflow, #Torch, #PyTorch, #Theano

Notable researchers, papers and even #datasets. It is a great place to start reviewing your knowledge or learning something new.

Link: https://hackmd.io/@chanderA/aiguide

#wheretostart #entrylevel #novice #studycontent #studymaterials #books #MOOC #meta

🔥 Tensorflow 2.0 release

Faster
TPU support
TensorFlow datasets

Change log: https://medium.com/tensorflow/tensorflow-2-0-is-now-available-57d706c2a9ab

#google #tensorflow #dl #tf

​​GANs from Scratch 1: A deep introduction.

Great introduction and tutorial. With code in PyTorch and TensorFlow

Link: https://medium.com/ai-society/gans-from-scratch-1-a-deep-introduction-with-code-in-pytorch-and-tensorflow-cb03cdcdba0f

#tensorflow #pytorch #GAN #tutorial #entrylevel #novice #wheretostart

🎓 Reinforcement Learning Course from OpenAI

Reinforcement Learning becoming significant part of the data scientist toolbox.
OpenAI created and published one of the best courses in #RL. Algorithms implementation written in #Tensorflow.
But if you are more comfortable with #PyTorch, we have found #PyTorch implementation of this algs

OpenAI Course: https://spinningup.openai.com/en/latest/
Tensorflow Code: https://github.com/openai/spinningup
PyTorch Code: https://github.com/kashif/firedup

#MOOC #edu #course #OpenAI

Applying deep learning and Tensorflow to improve brain MRI images quality

Taking brain MRI images is complicated procedure as the orientation, location, and coverage needs to be correct in all three spatial dimentsions. The quality and consistency of positioning and orientation of the slices relies heavily on the skill and experience of the scan operator. This process can be time-consuming and difficult, especially for complex anatomies. As a result, there can be inconsistencies from scan operator to scan operator. This lack of consistency can make the job of the radiologist in interpreting these images more difficult especially when a patient is being scanned as a follow up to previous MRI exam and they are trying to identify subtle changes in anatomy or disease progression over time.

The researchers from GE Healthcare Magnetic Resonance Imaging team developed an approach to aid the scan operator. The approach is based on 3 deep neural networks, can be adopted to take MRI images of the other body parts and achieves 99.2% accuracy score. The researchers notice that Tensorflow significantly helped them to develop and deliver the approach to the production.

Medium article: https://medium.com/tensorflow/intelligent-scanning-using-deep-learning-for-mri-36dd620882c4
GE Helthcare website: https://www.gehealthcare.com

#Tensorflow #medicine #casestudy #DL #CV

With new TensorBoard.dev you can share your DL/ML experiments result at tensorBoard

Link: https://blog.tensorflow.org/2019/12/introducing-tensorboarddev-new-way-to.html

#DL #ML #tensorflow #tf