Machine Learning for Art
ml4a is a collection of tools and educational resources which apply techniques from machine learning to arts and creativity.
![Fundamentals of machine learning](/images/guides/fundamentals.jpg)
Fundamentals of machine learning
Mathematical essentials for machine learning.
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![Essentials of Python](/images/guides/intro_python.jpg)
![Foundational mathematics](/images/guides/math_review_numpy.jpg)
Foundational mathematics
A review of relevant concepts from linear algebra and calculus, and intro to Numpy.
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![Classification & k-Nearest Neighbors](/images/guides/classification_kNN.jpg)
Classification & k-Nearest Neighbors
Introduction to classification using k-nearest neighbors algorithm
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![](/images/icons/colab.png)
![Linear regression](/images/guides/linear_regression.jpg)
Linear regression
Modeling data with line of best fit, basic gradient descent
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![](/images/icons/colab.png)
![DIY neural network](/images/guides/diy_neural_network.jpg)
![Neural networks in Keras](/images/guides/simple_neural_networks.jpg)
![Neural nets for classification](/images/guides/keras_classification.jpg)
Neural nets for classification
How to apply neural networks for classification
![](/images/icons/github.png)
![](/images/icons/colab.png)
![Convolutional neural networks](/images/guides/convolutional_neural_networks.jpg)
![Transfer learning](/images/guides/transfer_learning.jpg)