morvanzhou/tutorials

★ 12,915PythonAudience · generalComplexity · 1/5Setup · easy

Mindmap

mindmap
  root((morvan tutorials))
    Content areas
      Python basics
      Machine learning
      Data tools
      Git and Linux
    ML frameworks
      TensorFlow
      PyTorch
      Keras
      scikit-learn
    Data tools
      NumPy
      Pandas
      Matplotlib
    Audience
      Chinese learners
      ML beginners
    Format
      Video plus code
      Companion exercises

mindmap root((morvan tutorials)) Content areas Python basics Machine learning Data tools Git and Linux ML frameworks TensorFlow PyTorch Keras scikit-learn Data tools NumPy Pandas Matplotlib Audience Chinese learners ML beginners Format Video plus code Companion exercises

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Things people build with this

USE CASE 1

Follow along with machine learning tutorials using working Python code for TensorFlow or PyTorch.

USE CASE 2

Learn Python multithreading and multiprocessing with practical runnable code examples.

USE CASE 3

Study reinforcement learning concepts with hands-on code alongside companion video lessons.

Tech stack

PythonTensorFlowPyTorchKerasscikit-learnNumPyPandasMatplotlib

Getting it running

Difficulty · easy Time to first run · 30min

README and explanations are in Chinese, requires installing Python and the relevant ML framework for whichever tutorial section you choose.

In plain English

This repository contains a large collection of Python and machine learning tutorials created by Morvan Zhou, who runs the educational site mofanpy.com (also known as MofanPython). The README is written in Chinese, and the tutorials are aimed at Chinese-speaking learners who want to pick up programming and machine learning skills. The content is organized into several main categories. Python basics covers the fundamentals of the language along with topics like multithreading, multiprocessing, and building simple graphical interfaces. Machine learning covers a wide range, including an introduction to the subject, reinforcement learning (where a program learns by trial and reward), evolutionary algorithms like genetic algorithms, and hands-on examples using popular frameworks including TensorFlow, PyTorch, Theano, Keras, and scikit-learn. Data handling covers numerical computing with NumPy and Pandas, drawing charts with Matplotlib, and web scraping. There are also introductory tutorials on Git for version control and Linux basics. The code in this repository accompanies video tutorials that the author recorded and published on their website. The idea is that learners watch the video and follow along with the corresponding code. The author notes that these tutorials were created in their spare time and asks people who find them helpful to share them and consider supporting the project. If you are not a Chinese speaker, the README itself will be difficult to read, but the code files in the repository are in Python and may be understandable on their own. The topics covered are standard machine learning and Python programming subjects, so a developer could likely navigate the file structure and examples without the written explanations.

Copy-paste prompts

Prompt 1

I'm a beginner wanting to learn PyTorch using the Morvan Zhou tutorials. Which folder in the repo should I start with, and what are the first exercises?

Prompt 2

The morvanzhou/tutorials repo has reinforcement learning examples. Show me how to run the Q-learning example and explain what each part of the code does.

Prompt 3

I want to practice NumPy using the code from the Morvan Zhou tutorials. Give me the first five exercises I should work through and what concepts they cover.

Prompt 4

I found a TensorFlow example in the morvanzhou/tutorials repo but it uses TensorFlow 1.x syntax. Help me convert it to TensorFlow 2.x.

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