Getting Started with Machine Learning Tutorials #134

machine-learning
|── introduction
|    |── what-is-ml.mdx
|    |── role-of-ml-engineer.mdx
|    |── ml-engineer-vs-ai-engineer.mdx
|    |── skills-and-responsibilities.mdx
|    |── ml-lifecycle.mdx
|
|── mathematics-for-ml
|    |── linear-algebra
|    |    |── scalars.mdx
|    |    |── vectors.mdx
|    |    |── matrices.mdx
|    |    |── tensors.mdx
|    |    |── matrix-operations.mdx
|    |    |── determinants.mdx
|    |    |── inverse-of-matrix.mdx
|    |    |── eigenvalues-and-eigenvectors.mdx
|    |    |── svd.mdx
|    |
|    |── calculus
|    |    |── derivatives.mdx
|    |    |── partial-derivatives.mdx
|    |    |── chain-rule.mdx
|    |    |── gradients.mdx
|    |    |── jacobian.mdx
|    |    |── hessian.mdx
|
|    |── discrete-mathematics
|    |    |── sets-and-relations.mdx
|    |    |── logic.mdx
|    |    |── combinatorics.mdx
|    |    |── graphs.mdx
|
|── statistics
|    |── basic-concepts.mdx
|    |── descriptive-statistics.mdx
|    |── data-visualization.mdx
|    |── inferential-statistics.mdx
|
|── probability
|    |── basics-of-probability.mdx
|    |── conditional-probability.mdx
|    |── bayes-theorem.mdx
|    |── random-variables.mdx
|    |── pdf-pmf.mdx
|    |── probability-distributions.mdx
|
|── programming-fundamentals
|    |── python.mdx
|    |── basic-syntax
|    |    |── variables-and-data-types.mdx
|    |    |── data-structures.mdx
|    |    |── loops.mdx
|    |    |── conditionals.mdx
|    |    |── exceptions.mdx
|    |    |── functions.mdx
|    |── object-oriented-programming.mdx
|    |── essential-libraries
|    |    |── numpy.mdx
|    |    |── pandas.mdx
|    |    |── matplotlib.mdx
|    |    |── seaborn.mdx
|
|── data-engineering-basics
|    |── data-collection.mdx
|    |── data-formats.mdx
|    |── data-cleaning-and-preprocessing
|    |    |── handling-missing-data.mdx
|    |    |── feature-engineering.mdx
|    |    |── feature-scaling.mdx
|    |    |── normalization.mdx
|    |    |── dimensionality-reduction.mdx
|    |    |── feature-selection.mdx
|
|── machine-learning-core
|    |── types-of-machine-learning.mdx
|    |── supervised-learning
|    |    |── regression
|    |    |── classification
|    |    |── tree-based-models
|    |── unsupervised-learning
|    |    |── clustering.mdx
|    |    |── dimensionality-reduction.mdx
|    |── reinforcement-learning
|
|── model-evaluation
|    |── metrics
|    |    |── accuracy.mdx
|    |    |── precision.mdx
|    |    |── recall.mdx
|    |    |── f1-score.mdx
|    |    |── roc-auc.mdx
|    |    |── log-loss.mdx
|    |    |── confusion-matrix.mdx
|    |── validation-techniques
|    |    |── train-test-split.mdx
|    |    |── k-fold-cross-validation.mdx
|    |    |── loocv.mdx
|
|── deep-learning
|    |── neural-network-basics
|    |── cnn
|    |── rnn
|    |── attention-mechanisms
|    |── autoencoders.mdx
|    |── gans.mdx
|
|── advanced-ml-topics
|    |── natural-language-processing
|    |── explainable-ai
|    |── mlops
|    |── ai-agents
|
|── projects-and-case-studies
|    |── beginner-projects.mdx
|    |── intermediate-projects.mdx
|    |── advanced-projects.mdx
|    |── industry-case-studies.mdx