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accumulatemore/cv

★ 21,103Jupyter NotebookAudience · developerComplexity · 2/5ActiveSetup · easy

TLDR

Comprehensive deep learning study notes covering computer vision, NLP, large language models, and AI agents, organized as Jupyter Notebooks with accompanying video courses.

Mindmap

mindmap
  root((repo))
    What it covers
      Computer vision
      NLP and LLMs
      AI agents
      PyTorch basics
    How to use it
      Open in Jupyter
      Follow video courses
      Work through notebooks
    Learning resources
      Study notes 100-409
      Shared datasets
      Community discussion
    Support
      Career guidance
      Company referrals
      Self-learner community

Things people build with this

USE CASE 1

Learn computer vision fundamentals by working through numbered notebook sections paired with video lectures.

USE CASE 2

Study deep learning theory and practice with hands-on PyTorch exercises across multiple course tracks.

USE CASE 3

Explore large language models and AI agent design through dedicated notebook modules.

USE CASE 4

Access shared datasets and join a community of self-learners studying the same material.

Tech stack

Jupyter NotebookPythonPyTorchAnaconda

Getting it running

Difficulty · easy Time to first run · 5min
License could not be detected automatically. Check the repository's LICENSE file before use.

In plain English

This repository is a comprehensive set of deep learning study notes covering computer vision, natural language processing, large language models, and AI agents. The notes are organized in numbered sections: notes 100-122 accompany a PyTorch video course, notes 200-268 accompany a deep learning video course, notes 300-354 accompany another deep learning course, and notes 400-409 cover large model agents. The materials are presented as Jupyter Notebook files intended to be opened with Anaconda's Jupyter Notebook rather than in PyCharm, as images and formulas may not render correctly in some editors. Datasets used in the courses are shared via a Baidu Pan link with an extraction code. The project also includes a community discussion group for self-learners and offers career guidance resources, including internal referrals to major Chinese technology companies. The description notes the project is complete. Topics tagged include computer vision, deep learning, agents, and Jupyter Notebook.

Copy-paste prompts

Prompt 1
I want to learn PyTorch and computer vision. How do I start with the notes 100-122 section and what should I do in each notebook?
Prompt 2
Show me how to set up Anaconda and Jupyter Notebook to properly view the formulas and images in these deep learning study notes.
Prompt 3
I'm interested in large language models and AI agents. Which notebooks in the 400-409 range should I work through first?
Prompt 4
How can I download the datasets from Baidu Pan and use them with the notebooks in this repository?
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