Tensorflow Tutorial : Part 2 – Getting Started

Tensorflow Tutorial : Part 2 – Getting Started

  • This post is the second part of the multi-part series on a complete tensorflow tutorial – – – If you have tensorflow already installed, you can just skip to the next section.
  • Below we have the different data types in supported by Tensorflow.
  • Note: Quantitized values [qint8, qint16 and quint8] are special values for tensorflow that help reduce the size of the data.
  • In fact, Google has gone to the extent of introducing Tensorflow Processing Units (TPUs) to speed up computation by leveraging quantitized values – – We will quickly generate some data to get started.
  • In the next part, we will finally be ready to train our first tensorflow model on house prices.

In this multi-part series, we will explore how to get started with tensorflow. This tensorflow tutorial will lay a solid foundation to this popular tool that…
Continue reading “Tensorflow Tutorial : Part 2 – Getting Started”

Tensorflow Tutorial : Part 2 – Getting Started

Tensorflow Tutorial : Part 2 – Getting Started #abdsc

  • This post is the second part of the multi-part series on a complete tensorflow tutorial – – – If you have tensorflow already installed, you can just skip to the next section.
  • Below we have the different data types in supported by Tensorflow.
  • Note: Quantitized values [qint8, qint16 and quint8] are special values for tensorflow that help reduce the size of the data.
  • In fact, Google has gone to the extent of introducing Tensorflow Processing Units (TPUs) to speed up computation by leveraging quantitized values – – We will quickly generate some data to get started.
  • In the next part, we will finally be ready to train our first tensorflow model on house prices.

In this multi-part series, we will explore how to get started with tensorflow. This tensorflow tutorial will lay a solid foundation to this popular tool that…
Continue reading “Tensorflow Tutorial : Part 2 – Getting Started”

Google Machine Learning Models for Image Captioning Ported to TensorFlow and Open-Sourced

.@google open-sources a TensorFlow model for image captioning

  • Google Machine Learning Models for Image Captioning Ported to TensorFlow and Open-Sourced
  • The model comes up with a caption that hadn’t previously existed.
  • The model appears to address this problem by introducing a fine-tuning phase that allows the model to extract information useful for describing details of objects, exclusive of the classification phase.
  • Google chronicled their journey over the past few years with their announcement around open-sourcing a TensorFlow model for image captioning, and some of the testing for comparing accuracy and performance benchmarks between the new approach and existing implementations.
  • It splits the image classification phase for identifying objects from another phase that adds adjectives and prepositional phrases, and from a phase in which the model gives the caption structure to make it more syntactically correct and humanlike.

As TensorFlow becomes more widely adopted in the machine learning and data science domains, existing machine learning models and engines are being ported from existing frameworks to TensorFlow for improved performance, furthering the adoption and success of the open-sourced project.
Continue reading “Google Machine Learning Models for Image Captioning Ported to TensorFlow and Open-Sourced”