[TensorFlow] Introduction to TensorFlow Datasets and Estimators

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[TensorFlow] Introduction to TensorFlow Datasets and Estimators

Datasets and Estimators are two key TensorFlow features you should use: Datasets: The best practice way of creating input pipelines (that is, reading data into your program). Estimators: A high-level way to create TensorFlow models. Estimators includ…

吴恩达课后习题第二课第三周：TensorFlow Introduction

目录第二课第三周:TensorFlow Introduction Introduction to TensorFlow 1 - Packages 1.1 - Checking TensorFlow Version 2 - Basic Optimization with GradientTape 2.1 - Linear Function Exercise 1 - linear_function 2.2 - Computing the Sigmoid Exercise 2 - sigmoid 2…

Introduction to TensorFlow

Lecture note 1: Introduction to TensorFlow Why TensorFlow TensorFlow was originally created by researchers at Google as a single infrastructure for machine learning in both production and research. Later, an implementation of it was open sourced unde…

移动端目标识别(３)——使用TensorFlow Lite将tensorflow模型部署到移动端(ssd)之Running on mobile with TensorFlow Lite　（写的很乱，回头更新一个简洁的版本）

承接移动端目标识别(2) 使用TensorFlow Lite在移动设备上运行在本节中,我们将向您展示如何使用TensorFlow Lite获得更小的模型,并允许您利用针对移动设备优化的操作. TensorFlow Lite是TensorFlow针对移动和嵌入式设备的轻量级解决方案.它支持端上的机器学习推理,具有低延迟和小二进制模型大小. TensorFlow Lite使用了许多技术,例如允许更小和更快(定点数学)模型的量化内核. 对于本节,您需要从源代码构建TensorFlow…

移动端目标识别(1)——使用TensorFlow Lite将tensorflow模型部署到移动端(ssd)之TensorFlow Lite简介

平时工作就是做深度学习,但是深度学习没有落地就是比较虚,目前在移动端或嵌入式端应用的比较实际,也了解到目前主要有 caffe2,腾讯ncnn,tensorflow,因为工作用tensorflow比较多,所以也就从tensorflow上下手了. 下面内容主要参考&翻译: https://www.tensorflow.org/mobile/?hl=zh-cn https://github.com/tensorflow/models/blob/master/research/object_detect…