项目作者: NirantK
项目描述 :
精选的机器学习,NLP,愿景,推荐系统项目理念
高级语言:
项目地址: git://github.com/NirantK/awesome-project-ideas.git
Awesome Deep Learning Project Ideas

A curated list of practical deep learning and machine learning project ideas
- 30+ ideas
- Relevant to both the academia and industry
- Ranges from beginner friendly to research projects
Contents
Hackathon Ideas - Project ideas unlocked by use of Large Language Models, specially text to text — note that a lot of the text to text ideas can also be buit a lot better with LLMs now!
Text - With some topics about Natural language processing
Forecasting - Most of the topics in this section is about Time Series and similar forecasting challenges
Recommendation Systems
Vision - With topics about image and video processing
Music and Audio - These topics are about combining ideas from language and audio to understand music
Conclusion
Hackathon Ideas
Developer Ideas
- Text to cmd for terminal: Take user intent in terminal e.g.
$ask "how to list all files with details"
> Execute "ls -l"? [y/N] y
$ls -l
Build and edit YAMLs using natural language e.g. Kubernetes and other form of config files
- Kor for ideas on how this is done for JSON
- Can be use-case specific. Build pipelines? Kube?
Mobile Android/iOS SDK for Stable Diffusion inference
Voice powered Experiences
- Audio Conversation with chatGPT, can combine with fast Text-to-Speech e.g. Eleven Labs to have a two-way conversation
- Telegram/WhatsApp bot to get audio and save as text with metadata into mem.ai or Roam Research or Obsidian
Edit image by giving instructions of what you want to do: SeeChatGPT and playgroundai.com as examples
Semantic search over any media
Text to Music Generation
Knowledge Base QA aka Answer Engines
- Take any plaintext dataset e.g. State of the Union address and build on top of that

- Can use this over Video Subtitles to search and QA over videos as well, by mapping back to source
Guided Summarisation/Rewriting
- Take specific questions which the user might have about a large text dataset e.g. a novel or book and include that in your summary of the piece
- Pay attention to specific entities and retell the events which happen in a story with attention to that character
ControlNet + Stable Diffusion for Aethetic Control
- Build tooling using diffusers which takes in a set of photos, finetunes a model (LoRA) on a person, detects face and moves it to a new aesthetic e.g. futuristic neon punk, grunge rock, Studio Ghibli. Can also add InstructPix2Pix to give user more control.
Text to Code/SQL
- Use code understanding to convert use query to SQL or another executable programming language, including Domain Specific Languages
- Here is an example of the same: qabot
Text
Natural Language Understanding
Sentence to Sentence semantic similarity
- Can you identify question pairs that have the same intent or meaning?
- Dataset: Quora question pairs with similar questions marked
Fight online abuse
Open Domain question answering
Automatic text summarization
- Can you create a summary with the major points of the original document?
- Abstractive (write your own summary) and Extractive (select pieces of text from original) are two popular approaches
- Dataset: CNN and DailyMail News Pieces by Google DeepMind
Copy-cat Bot
- Generate plausible new text which looks like some other text
- Obama Speeches? For instance, you can create a bot which writes some @samim/obama-rnn-machine-generated-political-speeches-c8abd18a2ea0">new speeches in Obama’s style
- Trump Bot? Or a Twitter bot which mimics @realdonaldtrump"">@realDonaldTrump
- Narendra Modi bot saying “doston“? Start by scrapping off his Hindi speeches from his personal website
- Example Dataset: English Transcript of Modi speeches
Check mlm/blog for some hints.
Forecasting
Recommendation systems
Vision
Image classification
- Object recognition or image classification task is how Deep Learning shot up to it’s present-day resurgence
- Datasets:
- Diagnosing and Segmenting Brain Tumors and Phenotypes using MRI Scans
- Dataset: MICCAI Machine Learning Challenge aka MLC 2014
- Identify endangered right whales in aerial photographs
- Can computer vision spot distracted drivers?
Bone X-Ray competition
- Can you identify if a hand is broken from a X-ray radiographs automatically with better than human performance?
- Stanford’s Bone XRay Deep Learning Competition with MURA Dataset
Image Captioning
- Can you caption/explain the photo a way human would?
- Dataset: MS COCO
Image Segmentation/Object Detection
Large-Scale Video Understanding
- Can you produce the best video tag predictions?
- Dataset: YouTube 8M
Video Summarization
Style Transfer
- Can you recompose images in the style of other images?
- Dataset: fzliu on GitHub shared target and source images with results
Chest XRay
- Can you detect if someone is sick from their chest XRay? Or guess their radiology report?
- Dataset: MIMIC-CXR at Physionet
Clinical Diagnostics: Image Identification, classification & segmentation
- Can you help build an open source software for lung cancer detection to help radiologists?
- Link: Concept to clinic challenge on DrivenData
Satellite Imagery Processing for Socioeconomic Analysis
Satellite Imagery Processing for Automated Tagging
- Can you automatically tag satellite images with human features such as buildings, roads, waterways and so on?
- Help free the manual effort in tagging satellite imagery: Kaggle Dataset by DSTL, UK
Music
FAQ
Can I use the ideas here for my thesis?
Yes, totally! I’d love to know how it went.
Do you have any advice before I start my project?
Advice for Short Term Machine Learning Projects by Tim R. is a pretty good starting point!
How can I add my ideas here?
Just send a pull request and we’ll discuss?
Hey, something is wrong here!
Yikes, I am sorry. Please tell me by raising a GitHub issue.
I’ll fix it as soon as possible.
Acknowledgements
Problems are motivated by the ones shared at:
Credit
Built with lots of keyboard smashing and copy-pasta love by NirantK. Find me on @nirantk">Twitter!
License
This repository is licensed under the MIT License. Please see the LICENSE file for more details.