Quizzes
Recognition is not understanding. These quizzes ask you to calculate, diagnose bugs, order processes, and make design calls. Missed questions go into your review queue.
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Calculus for ML6 questions · Calculus for MLInformation theory10 questions · Information theoryNumerical stability9 questions · Numerical stabilityProbability and statistics6 questions · Probability and statisticsThe Python toolkit6 questions · The Python toolkitVectors and matrices6 questions · Vectors and matricesLearning paradigms8 questions · Learning paradigmsThe language of ML6 questions · The language of MLWorkflow, splits, and leakage6 questions · Workflow, splits, and leakageOverfitting and the bias-variance trade-off6 questions · Overfitting and the bias-variance trade-offLinear regression9 questions · Linear regressionRegularization and regression metrics6 questions · Regularization and regression metricsClassification metrics and thresholds7 questions · Classification metrics and thresholdsLogistic regression6 questions · Logistic regressionK-nearest neighbors8 questions · K-nearest neighborsNaive Bayes6 questions · Naive BayesSupport vector machines6 questions · Support vector machinesDecision trees6 questions · Decision treesRandom forests and gradient boosting6 questions · Random forests and gradient boostingDBSCAN, hierarchical clustering, and Gaussian mixtures6 questions · DBSCAN, hierarchical clustering, and Gaussian mixturesK-means clustering8 questions · K-means clusteringPCA, t-SNE, and UMAP6 questions · PCA, t-SNE, and UMAPNamed entity recognition11 questions · Named entity recognitionFrom text to vectors6 questions · From text to vectorsTopic modeling10 questions · Topic modelingWord embeddings6 questions · Word embeddingsIntro to PyTorch10 questions · Intro to PyTorchLoss functions9 questions · Loss functionsThe neural-network forward pass8 questions · The neural-network forward passBackpropagation6 questions · BackpropagationGradient descent8 questions · Gradient descentDebugging neural networks10 questions · Debugging neural networksTraining and regularization6 questions · Training and regularizationAutoencoders, diffusion, and transfer learning6 questions · Autoencoders, diffusion, and transfer learningConvolutional networks6 questions · Convolutional networksFlow matching and rectified flows10 questions · Flow matching and rectified flowsGANs, generator versus discriminator10 questions · GANs, generator versus discriminatorLatent diffusion and Stable Diffusion10 questions · Latent diffusion and Stable DiffusionRecurrent networks, LSTMs, and GRUs6 questions · Recurrent networks, LSTMs, and GRUsAttention variants9 questions · Attention variantsBERT and masked language modeling9 questions · BERT and masked language modelingSelf-attention8 questions · Self-attentionThe transformer architecture6 questions · The transformer architectureAdapting LLMs6 questions · Adapting LLMsDecoding6 questions · DecodingFine-tuning in practice10 questions · Fine-tuning in practiceMixture of experts9 questions · Mixture of expertsOpen models: architecture walkthroughs9 questions · Open models: architecture walkthroughsScaling laws9 questions · Scaling lawsTokenization and pretraining6 questions · Tokenization and pretrainingThe RAG pipeline6 questions · The RAG pipelineVector search9 questions · Vector searchEvaluating LLM systems6 questions · Evaluating LLM systemsLLM inference10 questions · LLM inferenceServing LLMs11 questions · Serving LLMsAgent memory10 questions · Agent memoryModel Context Protocol10 questions · Model Context ProtocolMulti-agent systems9 questions · Multi-agent systemsBuilding reliable agents10 questions · Building reliable agentsTool use and agents10 questions · Tool use and agentsProduction architecture6 questions · Production architectureReliability, cost, and observability6 questions · Reliability, cost, and observabilitySecuring AI systems6 questions · Securing AI systemsDifferential privacy9 questions · Differential privacyFairness9 questions · FairnessExperimentation and A/B testing10 questions · Experimentation and A/B testingML system design10 questions · ML system designModel monitoring and drift10 questions · Model monitoring and driftThe portfolio project ladder6 questions · The portfolio project ladderThe 12-week plan6 questions · The 12-week planAnomaly detection10 questions · Anomaly detectionFeature engineering10 questions · Feature engineeringHyperparameter tuning10 questions · Hyperparameter tuningImbalanced data11 questions · Imbalanced dataTime series10 questions · Time seriesCLIP and contrastive image-text pretraining10 questions · CLIP and contrastive image-text pretrainingObject detection and YOLO9 questions · Object detection and YOLOSelf-supervised vision9 questions · Self-supervised visionSemantic segmentation and U-Net9 questions · Semantic segmentation and U-NetVision-language models9 questions · Vision-language modelsVision transformers9 questions · Vision transformersDeep Q-networks (DQN)10 questions · Deep Q-networks (DQN)MDPs, states, actions, and rewards9 questions · MDPs, states, actions, and rewardsPolicy gradients and REINFORCE9 questions · Policy gradients and REINFORCEProximal policy optimization (PPO)9 questions · Proximal policy optimization (PPO)Q-learning and SARSA9 questions · Q-learning and SARSACollective operations from scratch9 questions · Collective operations from scratchGradient checkpointing9 questions · Gradient checkpointingGradient clipping and mixed precision10 questions · Gradient clipping and mixed precisionScaling and distributed training10 questions · Scaling and distributed trainingZeRO and FSDP10 questions · ZeRO and FSDPContext engineering9 questions · Context engineeringFew-shot and chain-of-thought9 questions · Few-shot and chain-of-thoughtPrompt engineering9 questions · Prompt engineeringSpectrograms and mel features9 questions · Spectrograms and mel featuresSpeech recognition10 questions · Speech recognition: CTC, transducers, and attention