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"Cogito, ergo sum" (I think, therefore I am)

β€” RenΓ© Descartes

RenΓ© Descartes
Free Problems
Decimals, Fractions, and Real-World Math
This mixed practice explores decimal place value, fraction concepts, and real-world applications like gardening, road trips, and party planning through engaging scenarios.
28 pts Medium 104 Place Value Understanding Place Value System +3
Multi-Digit Multiplication Word Problems
A set of four real-world math problems involving multi-digit multiplication, covering garden planning, seating, fundraising, and area calculation to build number sense and operational fluency.
16 pts Medium 97 Multi-Digit Multiplication Number and Operations in Base Ten +3
Real-World Math Estimation & Planning
A set of practical math problems involving seating, fundraising, supply estimation, and resource planning in real-life scenarios like schools, stadiums, and communities.
28 pts Medium 96
Real-World Math Estimation & Planning
A set of practical math problems involving seating, fundraising, supply estimation, and resource planning in real-life scenarios like schools, concerts, and communities.
28 pts Medium 98 resource planning
Hyperbolic Functions: Definitions, Identities, Derivatives, and Inverses
This problem set covers the fundamental concepts of hyperbolic functions as explained in Professor Dave's video. You'll explore definitions, identities, derivatives, and inverses of hyperbolic functions, progressing from basic understanding to advanced applications. These functions are analogous to trigonometric functions but relate to hyperbolas rather than circles, and can be expressed using exponential terms.
28 pts Medium 103 hyperbolic functions exponential functions trigonometric identities +7
Knowledge Distillation: How LLMs train each other
This problem set explores the concept of knowledge distillation in large language models (LLMs), covering its historical origins, mathematical foundations, practical implementations, and modern applications. Based on the YouTube video "Knowledge Distillation: How LLMs train each other," these questions will test your understanding of how powerful teacher models transfer knowledge to smaller student models, the key differences between various distillation approaches, and the computational challenges involved in this process.
27 pts Medium 96 knowledge distillation large language models model training +7
Premium Problems
Python I/O and Data Pipeline Assessment - Part 4
20 questions focused on PyTorch Dataset/DataLoader design: map/iterable datasets, transforms, custom collate/padding, worker seeding/sharding, num_workers/pin_memory/prefetch_factor, caching, memmap/shared memory, batching by size, profiling, and performance tuning.
10.00 60 pts Medium 98 torch.utils.data.dataset pytorch dataset +7
Chapter 02 - Numeric Python
This problem set covers key concepts from Chapter 2: Vectors, Matrices, and Multidimensional Arrays. The problems test understanding of NumPy array fundamentals, including array creation, indexing, slicing, operations, and vectorized computing. Each question is designed to reinforce the core concepts presented in the chapter.
5.00 26 pts Medium 97 numpy-arrays array-attributes shape +7
USAAIO 2025 R1P3 - Logistic Regression Implementation
This problem focuses on implementing logistic regression from scratch using the Titanic dataset. You will work through data pre-processing, mathematical derivations, and implement both gradient descent and Newton's method for logistic regression. The dataset contains passenger information from the Titanic, and your goal is to predict survival based on various features.
10.00 48 pts Easy 93 data-loading pandas data-exploration +7
USAAIO 2025 R1P2 - Basics of Neural Network - From Linear Regression to DNN Training
This problem is about the basics of neural network. Each part has its particular purpose to intentionally test you something. Do not attempt to find a shortcut to circumvent the rule. And all coding tasks shall run on CPUs, **not GPUs**.
10.00 36 pts Easy 96 learning-rate-scheduler pytorch optimization +12
USAAIO 2025 R1P1 - Fibonacci Matrix Form
Let us consider the following sequence: $$ F_n = F_{n-1} + F_{n-2},\ \forall\ n \ge 2. $$
8.00 27 pts Medium 96 fibonacci sequence linear algebra matrix form +7
IAIO 2024 Part 2 - Machine Learning Algorithms and Deep Learning
This problem covers the remaining categories of the 2024 International Artificial Intelligence Olympiad (IAIO), focusing on machine learning algorithms and deep learning. You'll work through practical implementations of k-means clustering, deep learning architectures, and advanced machine learning theory including kernel methods and the Perceptron algorithm. The problems cover: - K-means clustering algorithm implementation and convergence - Deep learning architectures (DALL-E, Transformers) - Perceptron algorithm and kernel methods - Mathematical proofs and theoretical analysis - Parameter counting and computational complexity
10.00 44 pts Hard 99 k-means clustering euclidean distance machine learning +7

Knowledge Graphs

USA AI Olympiad

Explore competitive programming and AI contest preparation concepts

Grade 5 Math

Discover elementary mathematics concepts and learning paths

Featured PDFs

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Cover of System Design Interview: An Insider's Guide Volume 2
System Design Interview: An Insider's Guide Volume 2
116 questions 348 pts
Cover of System Design Interview: An Insider's Guide
System Design Interview: An Insider's Guide
108 questions 317 pts
Cover of UNICALLI: A UNIFIED DIFFUSION FRAMEWORK FOR COLUMN-LEVEL GENERATION AND RECOGNITION OF CHINESE CALLIGRAPHY
UNICALLI: A UNIFIED DIFFUSION FRAMEWORK FOR COLUMN-LEVEL GENERATION AND RECOGNITION OF CHINESE CALLIGRAPHY
10 questions 38 pts
Cover of The Principles of Deep Learning Theory
The Principles of Deep Learning Theory
107 questions 418 pts

Featured Books

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Cover of Acing the System Design Interview
Acing the System Design Interview
153 questions 456 pts
Cover of Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
190 questions 543 pts
Cover of Hands-On Machine Learning with Scikit-Learn and PyTorch
Hands-On Machine Learning with Scikit-Learn and PyTorch
200 questions 554 pts
Cover of Deep Reinforcement Learning Hands-On - Third Edition
Deep Reinforcement Learning Hands-On - Third Edition
222 questions 720 pts

Featured Videos

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Cover of Flow-Matching vs Diffusion Models explained side by side
Flow-Matching vs Diffusion Models explained side by side
10 questions 29 pts
Cover of Attention in transformers, step-by-step | Deep Learning Chapter 6
Attention in transformers, step-by-step | Deep Learning Chapter 6
10 questions 30 pts
Cover of Knowledge Distillation: How LLMs train each other
Knowledge Distillation: How LLMs train each other
10 questions 27 pts
Cover of Diffusion Model
Diffusion Model
10 questions 32 pts