Machine learning in your field
109 guides to how machine learning is used in a field, with real examples, how to learn it, the tools and public data to practise on, and a first project.
Starting and learning
Choose a starting point for your background and the decisions you want to understand.
- Machine learning for beginners
- Machine learning for non technical people
- Machine learning for interview
- Machine learning for engineers
- Machine learning for high school students
- Machine learning for executives
- Machine learning for kids
- Machine learning for mathematicians
- Machine learning for mechanical engineers
- Machine learning for product managers
- Machine learning for research
- Machine learning for good
Data and modeling
Connect targets, representations, statistics and evaluation to concrete modelling tasks.
- Machine learning for data science
- Machine learning for data analysis
- Machine learning for linear regression
- Machine learning for outlier detection
- Machine learning for unlabeled data
- Machine learning for causal inference
- Machine learning for econometrics
- Machine learning for optimization
- Machine learning for uncertainty quantification
- Machine learning for survival analysis
- Machine learning for time series data
- Machine learning for time series forecasting with Python
- Machine learning life cycle
- Machine learning workflow
- Machine learning X and Y
- Machine learning XOR problem
- Machine learning XGBoost Python
- Machine learning libraries for Python
- Machine learning XAI
- Machine learning for linear algebra
Business and operations
Explore prediction, inspection, planning and retrieval in operational workflows.
- Machine learning for business analytics
- Machine learning for predictive analytics
- Machine learning for operations
- Machine learning for data-driven last-mile delivery optimization
- Machine learning for quality control
- Machine learning for crop yield prediction
- Machine learning for libraries
- Machine learning for variance reduction in online experiments
Finance and economics
Study point-in-time data, forecasting, risk and research evaluation.
- Machine learning for finance
- Machine learning for economics
- Machine learning for algorithmic trading
- Machine learning for asset managers
- Machine learning for factor investing
- Machine learning for market making
- Machine learning for options trading
- Machine learning for stock market prediction
- Machine learning for stock selection
- Machine learning for realised volatility forecasting
Science and engineering
Connect physical measurements, simulations and observations to appropriate AI methods.
- Machine learning for computational science and engineering
- Machine learning for chemical engineering
- Machine learning for chemistry
- Machine learning for dynamical systems
- Machine learning for fluid mechanics
- Machine learning for geoscience
- Machine learning for geospatial analysis
- Machine learning for geophysics
- Machine learning for geology
- Machine learning for inverse problems and data assimilation
- Machine learning for in-situ monitoring during metal additive manufacturing
- Machine learning for internet of things
- Machine learning for materials science
- Machine learning for molecular simulation
- Machine learning for ocean modelling
- Reinforcement learning for optimal control
- Machine learning for physics
- Machine learning for physics and astronomy
- Machine learning for quantum computing
- Machine learning for quantum matter
- Machine learning for radar signal processing
- Machine learning for robotics
- Machine learning for remote sensing
- Machine learning for signal processing
- Machine learning for weather forecasting
- Machine learning for water quality prediction and uncertainty assessment
- Machine learning for wireless communications
Health and life sciences
Explore research applications with explicit targets, authorised data and independent validation.
- Machine learning for healthcare
- Machine learning for drug discovery
- Machine learning for functional protein design
- Machine learning for genomics
- Machine learning for life sciences
- Machine learning for microbiologists
- Machine learning for neural decoding
- Machine learning for neuroimaging with scikit-learn
- Machine learning for neuroscience
- Machine learning for protein engineering
- Machine learning for regulatory genomics
- Machine learning for X ray
Images, language and games
Follow image, text and sequential-decision tasks to the representations and models they need.
- Machine learning for computer vision
- Machine learning for image classification
- Machine learning for image processing
- Machine learning for inverse graphics
- Machine learning for natural language processing
- Machine learning for LLM
- Machine learning for OCR
- Machine learning for video analysis
- Machine learning for game AI
- Machine learning for fantasy football
- Machine learning for sports betting
- Machine learning YOLO
- Deep learning for unsupervised
- Deep learning for optimization
Software and platforms
Connect modelling foundations to programming environments and inference interfaces.