Mathematics and Stats for ML and Data Science
Which maths topics you actually need for ML and data science, mapped directly onto pandas, statsmodels, scikit-learn and Hugging Face code.
Which maths topics you actually need for ML and data science, mapped directly onto pandas, statsmodels, scikit-learn and Hugging Face code.
Four problems, each with a classical algorithm and its quantum counterpart placed next to it - where the speedup is proven, where it's quadratic instead of exponential, and where quantum buys nothing at all.
Quantum machine learning, quantum-assisted drug discovery and quantum sensors are starting to touch primary care.
The patents behind quantum search, quantum factoring and the first commercial quantum processor.
How a Hungarian journalist's 1943 patent became the foundation of the world's best-selling pen.
How machines learn to see from pixels to object detection with PyTorch.
Three software patents that changed the game.
An introduction to quantum computing: superposition, entanglement, gates, and error correction.
LLMs and evolutionary computation to automate the search for better quantum error-correcting codes.
How the abstract machinery of theoretical CS of complexity classes, automata, information theory turns out to be the right language for quantum computing.