Kuest AI

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Learn machine learning 10x faster with AI

From linear regression to neural networks and transformers, Kuest helps you understand the math and the code behind the models you train.

4.87on iOS13,917,000+students already study with Kuest

topics
10
Builds on
Python, linear algebra, statistics
Common libraries
scikit-learn, PyTorch
Leads to
Data science and ML engineering

See how Kuest teaches it

It asks before it tells, so you do the thinking and it sticks.

You: My fraud model gets 99% accuracy, but it never flags a single fraud case. How is that possible?
Kuest: Let's look at the data first. Roughly what fraction of your transactions are fraud?
You: About 1%.
Kuest: So what accuracy would a model get if it just predicted "not fraud" for everything?
You: 99%. Oh, so accuracy is hiding that it learned nothing.
Kuest: Right. With imbalanced classes, look at recall and precision for the fraud class, or the confusion matrix. What would recall be here?
You: Zero, because it catches none of the fraud cases.

On imbalanced data, accuracy can look great while the model misses the rare class; check precision, recall and the confusion matrix.

Students who lock in with Kuest

students
13,917,000+
App Store rating
4.87
countries
100+
  • From a C to an A in chem

    “I stopped copying answers and started actually getting it. My chem grade went from a C to an A in one semester.”

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  • 3 hours → 40 minutes

    “My notes turn into a quiz in seconds. What used to take me all night now takes one episode of a show.”

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  • Finally ready for the SAT

    “The plan told me exactly what to do each day. I walked in calm for the first time ever.”

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  • It never lets me skip a step

    “Annoying at first, lifesaver on test day. I could do every problem without it.”

    Freshman, Ohio
  • Better than my tutor

    “It's there at midnight, it's patient, and it costs less than one session with my old tutor.”

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  • My streak is at 94 days

    “The quests are ten minutes. I do them on the bus. Somehow I'm now the one explaining bio to my friends.”

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    “Talking out loud with the tutor fixed my pronunciation faster than a whole year of class.”

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  • Parent here: no more 9pm meltdowns

    “My son gets real help without me pretending I remember calculus, and I can see his progress every week.”

    Parent, Washington

The method

How to study AI & machine learning with Kuest

Machine learning makes sense when the intuition, the math and the code line up. For each model, explain what it assumes, sketch how it learns, then read real training output. Revisit core ideas like the bias-variance tradeoff often, since everything else builds on them.

  1. Paste your code or metricsTutor chat

    Share your scikit-learn or PyTorch code, the error or the training curves. Kuest asks what you expected and helps you diagnose the gap.

  2. See the mathGraphs

    Kuest graphs loss curves, decision boundaries and the sigmoid so the formulas have a picture.

  3. Trace a networkTeaching board

    The teaching board shows layers, weights and how gradients flow backward through a small network.

  4. Choose the right metricQuizzes

    Scenario quizzes ask which model, metric or fix fits a situation, the judgment that exams and interviews test.

  5. Review papers and lecturesPodcasts

    Turn lecture notes or a paper summary into a podcast you can listen to between classes.

  6. Fill the math gapsGap finder

    Kuest notices when linear algebra, probability or calculus is what's actually blocking you and brings those back.

What you'll cover

Tap a topic to learn it now.

  1. 01What machine learning isTell supervised, unsupervised and reinforcement learning apart with examples.
  2. 02Data preparationSplit data, scale features and encode categories without leaking the test set.
  3. 03Linear and logistic regressionFit, interpret and compare the two workhorse models.
  4. 04Loss functions and gradient descentExplain how a model learns by stepping downhill on a loss surface.
  5. 05Evaluating modelsChoose accuracy, precision, recall, F1 or ROC-AUC and read a confusion matrix.
  6. 06Overfitting and regularizationSpot overfitting and control it with regularization and cross-validation.
  7. 07Trees and ensemblesUse decision trees, random forests and gradient boosting and know when they shine.
  8. 08Unsupervised learningGroup data with k-means and reduce dimensions with PCA.
  9. 09Neural networksExplain layers, activations and backpropagation and train a small network.
  10. 10Transformers and responsible AIDescribe how attention and language models work and where bias and misuse come in.

Try asking

Tap a question and Kuest starts teaching it, step by step.

Helps you prepare for

  • Intro to machine learning courses
  • Deep learning courses
  • Machine learning interviews
  • AWS Certified AI Practitioner

A month of Kuest costs less than one hour with a tutor

Same patience, any hour, every subject. Or stay on the free plan for good.

Private tutor

$40–80for one hour

  • Booked days in advance
  • One subject per session
  • Stops when the hour ends

Kuest Plus

$10a month, billed yearly

  • Every subject and exam on this site
  • Any hour, as long as you need
  • Quizzes, flashcards, podcasts and mock exams

Study on any device

Phone, tablet or laptop. Your chats, plans and flashcards come with you.

Questions, answered

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