machine-learning
Machine learning algorithms and techniques
Learn standard approaches for handling array-valued features in traditional ML models through feature engineering techniques like statistical extraction, dimensionality reduction, and feature hashing.
Discover data formats for fine-tuning LLMs like CSV/JSONL prompts, RAG query-context triples, and top AI datasets from Hugging Face for training mini LLMs. Essential guide for instruction tuning and RAG systems.
Yes, hands-on mini-projects, effective Googling, and AI for tasks/debugging outperform syntax memorization in data science learning. Get tips for long-term retention, faster problem-solving, and building a portfolio with real projects like Titanic.
Discover when to regenerate embeddings after embedding model updates. Trade-offs include accuracy vs. compute cost, downtime. Strategies: incremental re-embedding, dual-indexing, versioning for vector databases and RAG systems.
Resolve TensorFlow C API TF_SessionPRun errors: 'Local rendezvous CANCELLED PRun cancellation' and 'Must run setup before partial runs'. Checklist, code patterns, Windows MinGW tips for efficient streaming inference with Keras SavedModel.
Forecast stepwise price time series with change point detection, regime-switching (HMM), and survival models. Includes pipeline, libraries, and evaluation tips.
Fix PyTorch Dataset and DataLoader for multivariate time series preprocessing from CSV. Ensure (B, V, L) shapes, avoid data leakage with proper scaling, and validate sliding windows for MAMBA models.
Learn how TensorFlow handles backpropagation through mixed real and complex-valued functions using Wirtinger derivatives, GradientTape, and complex-aware ops. Covers chain rule, domain boundaries, and practical tips for CVNNs in comms systems.
Learn how to convert tennis score strings like '6-4 6-2' into numerical features for Random Forest models. Step-by-step guide with code examples.
Learn how to fix sklearn StackingClassifier NotFittedError when using prefit models and pipelines. Complete troubleshooting guide.
Is training a time series regression model on snapshots closer to departure data leakage when predicting earlier? Learn validation strategies, feature rules, and pitfalls to avoid lookahead bias in forecasting final bookings.