MLDB is the Machine Learning Database. It’s the best way to get machine learning or AI into your applications or personal projects. Head on over to MLDB.ai to try it right now or see Running MLDB for installation details.
We’re happy to announce the immediate availability of MLDB version 2016.12.16.0.
This release contains 228 new commits and modified 823 files. On top of many bug fixes and performance improvements, here are some of the highlights of this release:
fft(data [,direction='forward' [,type='real']])function that performs a fast fourier transform on the given data.
devicesconfiguration argument to the
tensorflow.graphfunction to specify on which device the graph is allowed to run.
tan(x)are the normal trigonometric functions
atan(x)are the normal inverse trigonometric functions
atan2(x, y)returns the two-argument arctangent of
y, in other words the angle (in radians) of the point through
yfrom the origin with respect to the positive
tanh(x)are the normal hyperbolic functions
atanh(x)are the normal inverse hyperbolic functions
pi()returns the value of pi, the ratio of a circle’s circumference to its diameter, as a double precision floating point number.
e()returns the value of e, the base of natural logarithms, as a double precision floating point number.
concat(x, ...)function that takes several embeddings with identical sizes in all but their last dimension and join them together on the last dimension.
import.jsonprocedure now supports the
arraysconfiguration argument to specify how arrays should be encoded in the JSON output.
import.textprocedure now returns a
rowCountfield representing the number of rows that were imported, just as the
reshape()function now has a 3 argument form.
reshape(val, shape, newel)is similar to the two argument version of reshape, but allows for the number of elements to be different. If the number of elements increases, new elements will be filled in with the newel parameter.
uap-corelibrary to the latest version improving user agent patterns used by the
merge()dataset function now accepts a single dataset
svd.trainprocedure now supports all select expressions to specify it’s input data, instead of the restricted form of select statements.
row_datasethas been modified to return one row per column, and an
atom_datasetconstruct added with semantics similar to the original. The types of these datasets have been improved, with inference of the
valuetype and the
columntype is now path, not string.
sql.expressionobject has been improved to allow
autoInputparameters to be passed, bypassing the requirement for a row on output and input respectively.