Learning Notes¶
Choose a subject to start exploring the notes currently available in MkDocs.
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Probability¶
Probability theorems, distributions, statistical inference, regression, simulation, and exercises.
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Linear Algebra¶
Vector spaces, linear maps, matrices, linear equations, and eigenvalues.
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Linux¶
Command-line tools, regular expressions, containers, and Kubernetes.
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Programming Languages¶
SQL, C, C++, exercises, data structures, and algorithms.
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Time Series¶
Time-series characteristics, ARIMA models, exponential smoothing, simulations, and Python examples.
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Deep Learning¶
Optimization, neural-network architectures, recurrent layers, transformers, convolutional networks, and generative models.
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Machine Learning¶
Regression, classification, model selection, tree-based models, Bayesian methods, support vector machines, and clustering.
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Differential Equations¶
First- and higher-order ODEs, systems, series solutions, Laplace transforms, and exercises.
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Maths Miscellaneous¶
Short mathematical notes on integrals, exponents, number patterns, and remainders.
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Large Language Models¶
Finetuning and inference engineering for language, image, and video generation models.