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@tensorflow4u
In this special #AskTensorFlow episode live from #TFDevSummit 2019, @lmoroney and @dynamicwebpaige answer questions on using callbacks to cancel training, getting started with #TensorFlow 2.0, and more! Watch here → https://t.co/944r2Y3oFl https://t.co/Nx2RwGG7QR
Inside TensorFlow: get the details on the TF.data APIs, giving you lots of datasets with one line of code, straight from the team that built it! Watch here → https://t.co/f3Bv7JTcUb https://t.co/lSVuEK815l
RT @deeplearningai_: Even if you have a small dataset, you can still leverage existing models that have been trained on millions of images using transfer learning. Course 2 of the https://t.co/xXmpwE13wh TensorFlow Specialization teaches you how to implement it: https://t.co/03BewkausZ https://t.co/mBnikSH27u
TensorFlow CPU optimizations accelerate genomics computations in DeepVariant by >3x. Learn how in this blog from the Brain Genomics team ↓ https://t.co/Kl2UM8WoUI
RT @NVIDIAAIDev: Learn how to activate your #TensorCores in @TensorFlow with just 2 lines of code for up to 3X speedup on #AI training. Register here: https://t.co/HTgfLh5CTX
Colab notebooks for Swift for TensorFlow https://t.co/o5o9jU4igx #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #tensorflow
Simple Tensorflow implementation of "GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond" https://t.co/9az2SUq54X #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #tensorflow
In this episode of TensorFlow Meets, Megan Kacholia, TensorFlow Engineering Director shares how TensorFlow has evolved to become more developer friendly, the run-time options for developers, and the latest update on TensorFlow 2.0! Watch here → https://t.co/wPl1STZliO https://t.co/0eiOEbTBON
In this special #AskTensorFlow episode live from #TFDevSummit 2019, @lmoroney and @dynamicwebpaige answer questions on using callbacks to cancel training, getting started with #TensorFlow 2.0, and more! Watch here → https://t.co/L2rpgzAn9G https://t.co/J3NgvrX5AE
Converting Mask R-CNN Keras model to Tensorflow model and Serving model https://t.co/IadnLAE4Cb #tensorflow #neuralnetwork #keras
RT @TensorFlowWorld: Don't miss your chance to take the stage at the first #TFWorld. We're looking for case studies, technology deep-dives, and more. The call for speakers closes tomorrow, April 23. https://t.co/7FVbUVFPyd https://t.co/cDrFzfTrcc
In this video from #TFDevSummit 2019, @random_forests and @fastdotai founder, @jeremyphoward chat about the future of Swift for TensorFlow and the new Swift online course coming to https://t.co/oGJPRukZTH this June! Watch this TensorFlow Meets here → https://t.co/IIqd6GnFgq https://t.co/rAMRzOBsmV
Take an inside look into the #TensorFlow team’s own internal training sessions! Follow along as Skye Wanderman-Milne dives into Control Flow, from its low-level ops & base APIs, to the new “functional” ops in Control Flow v2. Watch here → https://t.co/ldW3xLQhIO https://t.co/61GiRdduDI
RT @chunmlpage: My new blog post is on air. Neural machine translation with Luong attention on @TensorFlow 2.0. Building complicated models is just as easy as stacking up Lego pieces with #Keras. Check it out below: https://t.co/X4LpY54kNY
Learn about the new @fastdotai library using Swift for #TensorFlow directly from @JeremyPHoward & @clattner_llvm at this upcoming @DataInstituteSF workshop. (Tickets for the course are priced at $500, and space is limited!) Sign up here ↓ https://t.co/IUW6Ze8GXZ
Data compression in TensorFlow https://t.co/uhuCDTCYTf #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #tensorflow
Create a real #TensorFlow production ML pipeline with this new #TFX step-by-step tutorial! It guides developers through the process from ingesting data and training a model, to deploying, and production. Get started here → https://t.co/d2lgRCZ1cZ https://t.co/qkKQFMA7rB