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Dive Into Dl Tensorflow2.0

Dive Into Dl Tensorflow2.0 is a Chinese-language learning project that adapts the implementations in the Chinese edition of Dive into Deep Learning from MXNet to TensorFlow 2.0. It provides Markdown book-related documentation and chapter Jupyter notebooks.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Dive Into Dl Tensorflow2.0 — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use the published documentation for reading, or clone the repository when you want to work with the chapter notebooks or render the documentation locally.

Who it is for

  • Learners interested in deep learning, particularly those studying with TensorFlow 2.0.
  • Readers with basic mathematics and Python knowledge who want to connect book material with notebook examples.

Documented uses

  • Read the project’s deep-learning material in a rendered web format.
  • Study chapter implementations in TensorFlow 2.0 notebooks.
  • Explore computer vision and natural-language-processing topics through the learning materials.
Before you choose

Requirements & limits

The repository is public and lists an Apache-2.0 license.

  • The documentation focuses mainly on the Chinese edition of the book; the project notes that its content may differ somewhat from the original.
  • The project recommends basic linear algebra, calculus, probability, and Python, while saying prior machine-learning or deep-learning experience is not required.
  • Reading the rendered documentation and running the notebooks are separate workflows; the project directs users to clone the repository to work with code.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Serve the documentation locally

Render the project’s Markdown documentation on a local server.

Before you start

  • Node Package Manager (npm)
  • Git

Steps

  1. Install Docsify CLI with the command below.

    Documented command
    npm i docsify-cli -g

  2. Clone the repository with the command below.

    Documented command
    git clone https://github.com/TrickyGo/Dive-into-DL-TensorFlow2.0

  3. Change into the cloned Dive-into-DL-TensorFlow2.0 directory.

  4. Run docsify serve docs.

Expected outcome

The project describes viewing the rendered documentation at `http://localhost:3000`.

Guide limitations

  • This procedure serves the documentation; running the chapter notebooks is a separate task.
Documentation 1 ↗Documentation 2 ↗
Evidence and transparency

Sources & review

Official repository ↗Guide documentation ↗
Source record details
Source availability
Active
Sources checked
16 October 2026
Original website title
TrickyGo/Dive-into-DL-TensorFlow2.0 · Official homepage title · retained in its source language
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