从零开始的TensorFlow神经网络

你将学到什么

课程概况

In this 2-hours long project-based course, you will learn how to implement a Neural Network model in TensorFlow using its core functionality (i.e. without the help of a high level API like Keras). You will also implement the gradient descent algorithm with the help of TensorFlow’s automatic differentiation. While it’s easier to get started with TensorFlow with the Keras API, it’s still worth understanding how a slightly lower level implementation might work in tensorflow, and this project will give you a great starting point.

In order to be successful in this project, you should be familiar with python programming, TensorFlow basics, conceptual understanding of Neural Networks and gradient descent.

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

课程大纲

Neural Network from Scratch in TensorFlow

Welcome to Neural Network from Scratch in TensorFlow! In this 2-hours long project-based course, you will learn how to implement a Neural Network model in TensorFlow using its core functionality (i.e. without the help of a high level API like Keras). You will also implement the gradient descent algorithm with the help of TensorFlow's automatic differentiation. While it’s easier to get started with TensorFlow with the Keras API, it’s still worth understanding how a slightly lower level implementation might work in tensorflow, and this project will give you a great starting point for the same.

课程项目

Create the Neural Network class

Create a forward pass function

Use the cross entropy loss with logits

Create a predict function

Create the main training mechanism and implement gradient descent with automatic differentiation

Break down data-set in batches

Apply the neural network model to solve a multi-class classification problem

Plot the training results