1. An apparatus comprising: a processor; memory accessible to the processor, the memory storing: training data including a plurality of data samples, each of the plurality of data samples expressed as an ordered pair including a feature vector and a classifier value; a distributed hash table, each entry of the distributed hash table including a key and a value, each key of the distributed hash table corresponding to a particular feature vector of the training data and each value corresponding to a particular classifier value associated with the respective feature vector after applying a hash function to the particular classifier value; a stochastic gradient descent module executable by the processor to determine a predictor vector that minimizes a primal objective function of a support vector machine by determining a local inner product of the predictor vector and a kernel mapping function vector for each of a number of iterations using the distributed hash table; and a packing strategy module executable by the processor to combine calculations of the local inner product for a subset of the number of iterations.