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Keras / Tensorflow
openFrameworks
Contribute!
  • How to contribute a guide to ml4a
Fundamentals of machine learning
  • What is machine learning?
  • Vectors, matrices, and tensors
  • Functions, derivatives, and gradient descent
Essentials of Python
  • Conditionals, variables, loops, and other basics
  • Data structures and classes
  • Functions and plotting
Foundational mathematics
  • Matrices, multivariate functions
  • Gradients and chain rule
  • Essential numpy operations
Classification & k-Nearest Neighbors
  • Classification tasks
  • k-Nearest Neighbors method
Linear regression
  • Fitting datasets with lines
  • Evaluation and measuring error
  • Introduction to gradient descent
DIY neural network
  • Deriving neural networks
  • Non-linear activation functions and layers
  • Implementation of gradient descent for neural nets
Neural networks in Keras
  • Introduction to Keras
  • Architecture of simple neural net
  • Training a neural net on toy data
Neural nets for classification
  • Softmax activations and cross-entropy loss
  • Using Keras for classification
Convolutional neural networks
  • Building neural networks with convolutional and pooling layers for image processing
  • Train a convnet to classify MNIST handwritten digits
Transfer learning
  • Using powerful pre-trained networks as feature extractors
  • Training own image classifier on top of a pre-trained network
QuickDraw dataset
  • Loading sketches from Google's QuickDraw dataset
  • Basic QuickDraw classifier in Keras
Recurrent neural networks
  • RNNs, LSTMs, and context
  • Setting up an LSTM to predict characters in text
Sequence to sequence models
  • How RNNs operate on sequences on both ends
  • Training LSTM for language translation
Reverse image search
  • Extract feature vectors from images with convnets
  • Find most similar images to query image
Find shortest path between two images
  • Construct a graph of images connected via k nearest neighbors
  • Determine shortest path through the graph between two query images
Clustering images with t-SNE
  • Extract feature vectors from images with convnets
  • Embed images in 2d space using a t-SNE over their feature vectors
Clustering sounds with t-SNE
  • Extract feature vectors from audio clips with librosa
  • Embed audio clips in 2d with a t-SNE over their feature vectors
Reverse text search
  • Text representation: bag-of-words, tf-idf
  • Latent semantic analysis
  • Search for similar documents
Wiki t-SNE
  • Latent semantic analysis on corpus of text documents
  • Generate a t-SNE grid from LSA embeddings
Neural net painter
  • Regression of x,y -> r,g,b from an image
  • Generating "paintings" from learned model
  • Making videos by interpolating between multiple painters
Word vectors
  • Embedding words in vector space
  • Geometric operations in word-vector space and analogies
  • Generate a t-SNE from a trained word2vec embedding
Eigenfaces
  • Run principal component analysis to compress a dataset of faces
  • Generate new faces by inverting the projection
Autoencoders
  • Training an autoencoder on the QuickDraw dataset
  • Generating latent space interplations from autencoders
Neural synthesis
  • How to visualize features in a trained neural net
  • Recreating Deepdream
  • Masking, distorting the canvas, and video feedback
Q-Learning
  • Introduction to the reinforcement learning problem
  • Implementing a Q-Learner for an agent
Deep Q-Networks
  • Deep Q-Networks for larger state spaces
  • Implementing and training DQN for paddle-ball game
BigGANs
  • Sampling new images from BigGAN
  • BigGAN interpolations videos
  • Arithmetic on GAN features
BigGAN tricks
  • Linear and hyperspherical latent space interpolation
  • Modulating background while holding foreground constant in generation
  • Working with truncation
GLOW
  • Encoding images of faces into GLOW
  • Adding and subtracting face attributes generatively
  • Interpolations between faces
Object segmentation
  • Segmenting objects from images with Mask-RCNN
  • Background removal
Audio classifier
  • Analyze MFCC distribution of incoming microphone audio
  • Train a real-time multi-class classifier of sounds
Audio t-SNE viewer
  • Navigate an interactive playback application of audio samples embedded in 2d via t-SNE algorithm (pre-analyzed)
ConvnetOSC
  • Extract feature vector from real-time webcam stream
  • Send image feature vector over OSC
Convnet classifier
  • Extract feature vectors from incoming webcam stream
  • Train a real-time multi-class classifier of images
Convnet regressor
  • Extract feature vectors from incoming webcam stream
  • Control a set of sliders via regression over feature vectors
Convnet viewer
  • Analyze an image or webcam stream with a convnet
  • View the network's activation maps layer-by-layer
Doodle classifier
  • Train an image classifier to recognize different categories of your drawings (doodles)
  • Send classification results over OSC to drive some interactive application
Face classifier
  • Use face tracker to analyze facial expressions or poses
  • Train a real-time multi-class classifier of facial expressions
Face regressor
  • Use face tracker to analyze facial expressions or poses
  • Train real-time regression to control sliders according to facial expression
Gobot
  • Scrape screen pixels and detect Go board position
  • Have a convnet make move recommendations for human player
Image t-SNE viewer
  • Navigate an interactive viewer of images embedded in 2d via t-SNE algorithm (pre-analyzed)
Image t-SNE live
  • t-SNE and assign to grid a dataset of images (in-application)
  • Navigate an interactive viewer containing the arranged images
pix2pix tutorial
  • A tutorial on neural image translation with pix2pix
  • A survey of creative works using pix2pix
Reverse image search (fast)
  • Extract feature vector in real-time from an image/video/webcam/screengrabber
  • Quickly retrieve k nearest neighbors to that image
Reverse object search
  • Detect salient objects in image/video/webcam stream
  • Quickly retrieve k nearest neighbors of each detected object
Yolo (fast object detection) live
  • Detect salient objects in image/video/webcam/screengrabber
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