Notebooks and code snipptets for testing various Data Science concepts.
/ctypes(efficient computations using C/C++)/dataflows(data and model pipelines)/dl(deep learning)/equations(math formulae and equations)/events(event-based programs)/interviewkit(useful code snippets and examples)/mldesign(ML experiment principles and mistakes)/models(ML modelling and function interpolation)/jax(efficient computations and probabilistic modelling)/plotly(interactive plotting)/timescaledb(time series SQL with TimescaleDB)/unsupervised(embeddings and clustering)
Each folder has its own requirements.txt.