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Free Problems
Chapter 04 - Backpropagation Intuitively - Core Concepts
This problem set explores the intuitive understanding of backpropagation as presented in the video "Backpropagation, intuitively | Deep Learning Chapter 3". The problems cover key concepts including gradient descent, sensitivity analysis, weight adjustments, and the backpropagation algorithm mechanics. Work through these problems to solidify your understanding of how neural networks learn through backpropagation.
27 pts Medium 95 neural networks backpropagation machine learning +7
Chapter 02 - Gradient Descent and Neural Network Learning
This problem set explores the fundamental concepts of gradient descent and how neural networks learn, based on the video "Gradient descent, how neural networks learn | Deep Learning Chapter 2". The problems cover cost functions, gradient descent optimization, network architecture, and the practical implications of neural network training.
25 pts Easy 95 neural networks cost function gradient descent +7
Chapter 01 - Transformers and Large Language Models
This problem set explores the fundamental concepts behind transformers, the technology powering large language models like GPT. Based on the video "Transformers, the tech behind LLMs | Deep Learning Chapter 5", these questions cover word embeddings, attention mechanisms, softmax, and the overall architecture of transformer models. Work through these problems to build a solid understanding of how modern AI language models process and generate text.
28 pts Medium 102 large language models transformers generative models +7
Chapter 01 - Neural Networks for Handwritten Digit Recognition
This problem set tests your understanding of neural networks for handwritten digit recognition, based on the concepts explained in the YouTube video about recognizing digits from 28x28 pixel images. The problems cover network structure, activation functions, weights and biases, and the mathematical foundations of neural networks.
23 pts Easy 104 neural networks handwritten digit recognition input layer +7
Chapter 01 - Fourier Transform Fundamentals
This problem set tests understanding of the Fourier Transform concepts explained in the 3Blue1Brown video spUNpyF58BY. The video introduces the Fourier Transform through an intuitive geometric approach using winding frequencies and center of mass calculations. Questions cover the core concepts, mathematical formulation, and practical applications demonstrated in the video.
28 pts Medium 102 fourier transform geometric interpretation complex exponentials +7
Chapter 01 - Laplace Transform Fundamentals - Video Analysis
This problem set tests understanding of the foundational concepts from the Laplace transform video, covering complex exponentials, differential equations, and the relationship between the S-plane and physical systems like the damped harmonic oscillator. Questions range from basic definitions to advanced applications of the concepts presented.
27 pts Medium 101 exponential functions laplace transforms mathematical constants +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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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
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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

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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