# Machine Learning using only Numpy

Here you cna find various exercises to different machine learning techniques. All exercises are inteded to be solved using only basic mathematical operations provided by numpy. This implies, that the exercises are on a very low level. Solving them will help you to gain (or extend) your knowledge about the most essential parts of the algorithms.

- exercise-matrix-vector-operations
- exercise-simple-linear-regression
- exercise-multivariate-linear-regression
- exercise-logistic-regression
- exercise-bias-variance-tradeoff
- exercise-images-data-augmentation-numpy
- exercise-bayes-rule
- exercise-expected-value
- exercise-inverse-transform-sampling
- exercise-entropy
- exercise-kullback-leibler-divergence
- exercise-natural-pairing
- exercise-multivariate-gaussian
- exercise-univariate-gaussian-basics
- exercise-univariate-gaussian-likelihood
- exercise-1d-gmm-em
- exercise-sensorfusion-and-kalman-filter-1d
- exercise-simple-example-for-EM
- exercise-pymc3-examples
- exercise-importance-sampling
- exercise-rejection-sampling
- exercise-variational-mean-field-approximation-for-a-simple-gaussian