Applied AI from Scratch

Supervised learning: classification and regression

• Bias-variance trade off
• Logistic regression as a classifier
• Measuring classifier performance
• Support vector machines
• Neural networks
• Random forests

• principal component analysis
• autoencoders

• convolutional neural networks for image analysis
• recurrent neural networks for time-structured data
• the long short-term memory cell

• image analysis
• forecasting complex financial series, such as stock prices,
• complex pattern recognition
• natural language processing
• recommender systems

• TensorFlow, Theano, Caffe and Keras
• AI at scale with Apache Spark: Mlib

• overfitting
• biases in observational data
• missing data
• neural network poisoning