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Free Problems
Chapter 03 - Deep Learning with PyTorch Fundamentals
This problem set covers fundamental concepts from Chapter 3: Deep Learning with PyTorch. You'll be tested on tensor operations, gradients, neural network building blocks, and PyTorch-specific concepts. These problems progress from basic to advanced difficulty and include conceptual, practical, and analytical questions.
21 pts Medium 102 pytorch tensor creation deep learning +7
Chapter 02 - OpenAI Gym API and Gymnasium Fundamentals
This problem set tests your understanding of the OpenAI Gym API and Gymnasium library concepts covered in Chapter 2. You'll explore environment creation, action/observation spaces, agent implementation, and wrapper functionality. These problems progress from basic concepts to more advanced implementation details.
20 pts Easy 99 gymnasium reinforcement learning machine learning +7
Elementary Math Practice - Expressions, Geometry, and Coordinates
This problem set covers key 5th grade mathematics concepts including numerical expressions with braces and brackets, coordinate plane graphing, symmetry in shapes, and finding missing factors in equations. Each question builds on fundamental skills to develop mathematical thinking and problem-solving abilities.
8 pts Easy 99 order of operations arithmetic expressions nested parentheses +7
Elementary Mathematics Practice Set
This problem set covers key 5th grade mathematics concepts including coordinate planes, algebraic expressions, geometric shapes, and problem-solving strategies. Work through these problems to practice your math skills!
19 pts Beginner 97 coordinate plane coordinate axes x axis +8
Fraction Fundamentals for Grade 5
This problem set covers essential fraction concepts for 5th grade mathematics. You'll practice comparing fractions, converting between mixed numbers and improper fractions, adding and subtracting fractions with unlike denominators, calculating areas with fractions, and solving fraction word problems. Work through each problem carefully and show your reasoning!
18 pts Easy 100 fractions equivalent fractions math fundamentals +7
Volume Mastery Challenge
This problem set challenges your understanding of volume concepts for rectangular prisms. You'll compare volumes using unit cubes, apply the additive property of volume, and solve complex real-world problems. These expert-level questions require creative thinking and deep conceptual understanding of volume measurement.
7 pts Easy 101 volume unit cubes geometry +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

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Featured PDFs

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Deep Reinforcement Learning Hands-On - Third Edition
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Attention in transformers, step-by-step | Deep Learning Chapter 6
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Knowledge Distillation: How LLMs train each other
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Diffusion Model
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Popular Topics

machine learning 56 deep learning 40 neural networks 35 reinforcement learning 33 system-design 28 grade5 27 optimization 14 large language models 13 attention mechanisms 13 combinatorics 13 system-architecture 13 natural language processing 12 aime problems 12 Number Sense 12 scalability 11 beginner 10 number theory 10 performance 10 transformers 9 capacity-planning 9
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