eBooks E-Books Neural networks – brief review of layers and backprop (M-I-T) Neural networks – basic element (M-I-T) Neural networks – activation functions (M-I-T) Nearest neighbor models (M-I-T) Reading bar charts: comparing two sets of data (K-A) Model-based learning (M-I-T) Identifying individuals, variables and categorical variables in a data set (K-A) Machine learning as optimization – gradient descent in one dimension (M-I-T) Creating a bar graph (K-A) Machine learning as optimization – gradient descent in multiple dimensions (M-I-T) Machine learning as optimization – framework (M-I-T) Logistic regression – setting and sigmoid function (M-I-T) Linear logistic classifier – negative log likelihood loss function (M-I-T) Decision trees (M-I-T) Linear logistic classifier – hypothesis class (M-I-T) Collaborative filtering – strategy (M-I-T) « Previous 1 … 2,346 2,347 2,348 2,349 2,350 … 4,276 Next »
