TensorFlow is an end-to-end open source platform for machine learning

In the featurization tutorial we incorporated multiple features into our models, but the models consist of only an embedding layer. We can add more dense layers...

In the featurization tutorial we incorporated multiple features beyond just user and movie identifiers into our models, but we haven't explored whether those fe...

Bert 全称为 Bidirectional Encoder Representations from Transformers（Bert）。和 ELMo 不同，BERT 通过在所有层联合调节左右两个上下文来预训练深层双向表示，此外还通过组装长句作为输入增强了对长程语义的理解。Bert ...

One of the great advantages of using a deep learning framework to build recommender models is the freedom to build rich, flexible feature representations.

In this tutorial, we build a simple matrix factorization model using the MovieLens 100K dataset with TFRS. We can use this model to recommend movies for a given...

上篇分享了一位30年编程经验的技术大佬，为什么选择离开google的几点原因。（作为大龄程序员，我为什么离开大厂？）

如上图所示，执行 pull 之后，我们看到本地已经存在 tensorflow/serving:latest

首先我们来介绍下数据集，该数据集有5种花，一共有3670张图片，分别是daisy、dandelion、roses、sunflowers、tulips，数据存放结构如下所示

This tutorial shows how to load and preprocess an image dataset in three ways. First, you will use high-level Keras preprocessing utilities and layers to read a...