Machine Learning
Machine learning from fundamentals to production
Open "ML Basics"
ML Basics
Supervised/unsupervised, metrics, train/val/test, regularization
39 questions
Open "Classical Algorithms"
Classical Algorithms
Linear/logistic, trees, RF, gradient boosting, SVM, k-means, PCA
25 questions
Open "Neural Networks"
Neural Networks
Perceptron, MLP, activations, backprop, optimizers
22 questions
Open "Deep Learning"
Deep Learning
CNN, RNN/LSTM, Transformer, attention, residual, transfer
20 questions
Open "NLP"
NLP
Tokenization, embeddings, BERT, GPT, fine-tuning, metrics
15 questions
Open "Computer Vision"
Computer Vision
CNN architectures, detection, segmentation, augmentation, ViT
25 questions
Open "MLOps"
MLOps
Experiment tracking, registry, deployment, monitoring, drift
31 questions
Open "ML in Frontend"
ML in Frontend
TensorFlow.js, ONNX Runtime Web, WebGPU, transformers.js
15 questions
Open "AI/ML Frameworks"
AI/ML Frameworks
PyTorch, TensorFlow, Hugging Face, LangChain, MLflow, vLLM, and companions
25 questions
Open "Data: NumPy & Pandas"
Data: NumPy & Pandas
NumPy, Pandas, Polars, broadcasting, vectorization
24 questions