YouTube Summarizer

Turn any YouTube video into structured study notes

Paste a link. Get notes, flashcards, a quiz, and a mind map — powered by Google Gemini. Works on lectures, podcasts, tutorials, and documentaries.

No credit card required · 15 free credits/month

10 secAverage time to first note
7 assetsGenerated per video
40+Supported languages
100%Free to start
Live output preview

Exactly what you'll get

This is real output from a Stanford CS231N lecture — the same format you'll see in your workspace.

SummaryFlashcardsMind MapQuizTranscript
STANDARD SUMMARY

CS231N Lecture 1: Introduction to CNNs

This lecture introduces Convolutional Neural Networks as a paradigm for visual recognition. It traces the history of computer vision from early edge-detection algorithms to modern deep learning pipelines, establishing why hierarchical feature learning outperforms hand-crafted features.

The Visual Recognition Problem

  • Human vision processes 10¹⁴ synaptic operations per second — replicating this computationally has been the central challenge since the 1960s.
  • Early attempts (Hubel & Wiesel, 1959) discovered simple and complex cells in the visual cortex, directly inspiring convolutional filter design.
  • Semantic gap: raw pixel values carry no inherent meaning; a model must learn invariant representations.

Why Deep Learning Broke Through

  • ImageNet (2009) provided 14M labelled images — the scale needed to train large models without overfitting.
  • AlexNet (2012) halved the top-5 error rate vs. the best non-DL approach, triggering industry-wide adoption.
  • GPUs unlocked the parallelism required: convolutions are matrix multiplications that map naturally onto CUDA cores.

Course Roadmap

  • Weeks 1–3: image classification, loss functions, optimisation (SGD, Adam).
  • Weeks 4–6: CNN architectures — LeNet, AlexNet, VGG, ResNet, Inception.
  • Weeks 7–10: detection (YOLO, Faster R-CNN), segmentation, and generative models.
Everything included

One link. Seven study assets.

Every YouTube video you process unlocks a full study workspace — not just a summary.

Structured Notes

Key ideas, section headings, and bullet-point takeaways — exactly what you'd write if you had unlimited time.

Flashcard Deck

Term-definition and concept cards auto-generated from the transcript. Spaced-repetition ready.

Quiz

Multiple-choice questions with explanations. Test yourself before the exam.

Mind Map

An interactive visual graph of how every concept in the video connects to every other.

How it works

Ready in under 30 seconds

01

Paste any YouTube URL

Lectures, podcasts, tutorials, documentaries — any public video with captions works. No time limit on captioned videos.

02

Gemini AI reads the content

The transcript is extracted, chunked, and fed to Google Gemini, which understands the context — not just the words.

03

Get your study workspace

Notes, flashcards, quiz, and mind map appear in a single clean workspace. Export to PDF whenever you're ready.

Who it's for

Built for anyone who learns from video

🎓

Students

Keep up with lecture recordings without watching them at 1x speed.

👨‍💻

Developers

Absorb conference talks and tutorials without pausing every 10 seconds.

📊

Professionals

Extract actionable insights from long webinars and industry talks.

🔬

Researchers

Process lecture series and seminar recordings faster than any other method.

Works in 40+ languages

Notelify auto-detects the video language and generates notes in the same language — or translates everything to English with one click.

FAQ

Common questions

How long can the YouTube video be?

Free users can summarise any video that has captions — there's no time limit on captioned content. For videos without captions (audio transcription), Pro users get up to 4 hours.

Does it work on non-English videos?

Yes. Notelify auto-detects the video language and can summarise in the original language or translate the output to English.

What if the video has no captions?

Notelify falls back to AI-powered audio transcription (Whisper) when captions aren't available. This uses more credits but works on any video.

Is the summary accurate?

Summaries are grounded in the actual transcript — the AI cannot hallucinate content that wasn't said in the video. You can always cross-check against the timestamped transcript in the same workspace.

Can I export the notes?

Yes — all plans include PDF export. Click the export button in the workspace to download a formatted PDF of your notes.

Stop re-watching. Start learning.

Join thousands of students who get more out of every YouTube video with Notelify.

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