function normalizeTensor(data, dataMean, dataStd) {
  return data.sub(dataMean).div(dataStd);
}
Given expected mean and standard deviation, normalizes a dataset by
subtracting the mean and dividing by the standard deviation.

@param {Tensor2d} data: Data to normalize. Shape: [batch, numFeatures].
@param {Tensor1d} dataMean: Expected mean of the data. Shape [numFeatures].
@param {Tensor1d} dataStd: Expected std of the data. Shape [numFeatures]

@returns {Tensor2d}: Tensor the same shape as data, but each column
normalized to have zero mean and unit standard deviation.