Turn TensorFlow functions into mathematical notations and diagrams
This is based on some helper classes I started writing, to help my self make less mistakes and understand the code better. It is still work in progress. I want to share the idea to see if it interests others.
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Swift for TensorFlow
Swift for TensorFlow is a result of first-principles thinking applied to machine learning frameworks, and works quite differently than existing TensorFlow language bindings. Whereas prior solutions are designed within the constraints of what can be achieved by a (typically Python or Lua) library, Swift for TensorFlow is based on the belief that machine learning is important enough to deserve first-class language and compiler support.
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Google’s TensorFlow AI framework adds Swift and JavaScript support
Google todayunveiled a slew of updates to its popular TensorFlow machine learning framework aimed at making it useful for a wider variety of developers and providing data scientists with new ways to get started building AI models.
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Listening for illegal logging chainsaws using TensorFlow
Our team has built the world’s first scalable, real-time detection and alert system for logging and environmental conservation in the rainforest. Building hardware that will survive in the rainforest is challenging, but we’re using what’s already there: the trees. We’ve hidden modified smartphones powered with solar panels—called “Guardian” devices—in trees in threatened areas, and continuously monitor the sounds of the forest, sending all audio up to our cloud-based servers over the standard, local cell-phone network.
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Deploy TensorFlow models
Don’t follow the TensorFlow docs since they explain how to setup a docker image and compile TF serving that takes forever. We can do much better. Some guy made a docker image with everything already compile on it, so we are going to use that one.
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Kaggle Tensorflow Speech Recognition Challenge
From November 2017 to January 2018 the Google Brain team hosted a speech recognition challenge on Kaggle. The goal of this challenge was to write a program that can correctly identify one of 10 words being spoken in a one-second long audio file. Having just made up my mind to start seriously studying data science with the goal of turning a new corner in my career, I decided to tackle this as my first serious kaggle challenge.
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Semantic Image Segmentation with DeepLab in Tensorflow
Today, we are excited to announce the open source release of our latest and best performing semantic image segmentation model, DeepLab-v3+ [1], implemented in Tensorflow. This release includes DeepLab-v3+ models built on top of a powerful convolutional neural network (CNN) backbone architecture [2, 3] for the most accurate results, intended for server-side deployment. As part of this release, we are additionally sharing our Tensorflow model training and evaluation code, as well as models already pre-trained on the Pascal VOC 2012 and Cityscapes benchmark semantic segmentation tasks.
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Building a Next Word Predictor in Tensorflow
Next Word Prediction or what is also called Language Modeling is the task of predicting what word comes next. It is one of the fundamental tasks of NLP and has many applications. You might be using it daily when you write texts or emails without realizing it.
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