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nirantk/awesome-project-ideas

9,087Audience · dataComplexity · 1/5Setup · easy

TLDR

A curated list of over 30 machine learning and deep learning project ideas for learners and practitioners, each paired with links to public datasets you can download and start training on.

Mindmap

mindmap
  root((awesome-project-ideas))
    Categories
      Text and NLP
      Forecasting
      Recommendation
      Vision
      Audio
    LLM projects
      Text to shell
      Knowledge base QA
      Text to SQL
      Text to music
    Audience
      ML learners
      Practitioners
      Hackathon builders
    Value
      Idea descriptions
      Dataset links
      Tool suggestions
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Code map

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Things people build with this

USE CASE 1

Pick a beginner NLP project like comment moderation or question tagging and find a ready-to-use public dataset for it.

USE CASE 2

Find a time-series forecasting idea, rainfall, electricity demand, complete with dataset references for a portfolio project.

USE CASE 3

Get starter tool suggestions for building LLM-powered apps like a plain-English-to-shell-command converter.

USE CASE 4

Browse computer vision project ideas like plant disease detection with linked datasets to train on.

Getting it running

Difficulty · easy Time to first run · 5min

In plain English

This repository is a curated list of project ideas for people learning or practicing machine learning and deep learning. It is not a library or a tool, it is a collection of prompts describing what you could build, along with pointers to public datasets you could use to build it. The list covers more than 30 ideas ranging from beginner-friendly tasks to research-level problems. The ideas are organized into several categories. The text and natural language section includes things like automatically tagging forum questions, detecting abusive comments, answering questions from a document, summarizing long articles, and detecting whether two questions mean the same thing. Each entry names a relevant public dataset you can download and train on. A forecasting section covers predicting time series data such as rainfall, air quality, electricity demand, and blood donation likelihood. A recommendation systems section includes building a movie recommender using ratings data or a book recommender. A vision section covers tasks like identifying plant diseases from photos, detecting objects in satellite imagery, and recognizing lip movements from video. A hackathon ideas section, added more recently, focuses on projects that make use of large language models, such as a command-line tool that takes plain-English instructions and converts them to shell commands, knowledge base question answering, text-to-SQL, guided summarization, and text-to-music generation. These entries mention specific open-source tools and models that could serve as starting points. The README also includes a short music and audio section covering tasks like genre classification and automatic playlist generation. No code is included in the repository itself, the value is in the idea descriptions and dataset links.

Copy-paste prompts

Prompt 1
I want a machine learning portfolio project. From the awesome-project-ideas list, recommend the best beginner NLP idea and walk me through getting started with the linked dataset.
Prompt 2
I am learning recommendation systems. Give me a step-by-step plan to build the movie recommender idea from awesome-project-ideas using Python.
Prompt 3
I want to build the text-to-shell-command LLM project from awesome-project-ideas. Which open-source models and tools should I use to get started?
Prompt 4
Help me implement the duplicate question detection project from awesome-project-ideas using Sentence Transformers and the Quora dataset.
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