🚀 This release adds the capabilities to build binaries (wheels) that work across a large range of Linux distributions to our travis-ci. This will greatly benefit everyone who had issues with source installing fastFM.
Special thanks goes to
🚀 This release contains again various community contributions 😄 .
- 0️⃣ The default blas version has been changed from cblas to openblase (thanks @iramykytyn),
- 👍 python 3.6 support has been improved (thanks @chezou),
- warm start has been added to als classification (thanks @lucidfrontier45) and
- 🔄 changes in the numpy (thanks @mkdy) and sklearn api (thanks @takuti) have been incorporated.
🚀 The release further improves code quality by fixing a fair amount of coding style violations (thanks to @takuti ).
- fastFM has been accepted as contribution to the JMLR OSS track.
👍 fastFM supports now whatever BLAS version is installed (OpenBLAS is prefered).
🚀 This minor release updates the fastFM-core sub-module which contains a fix for #37 .
Previously the same random number generator seed was used for each start of the mcmc chain, which lead to bad mixing with warm start (
n_more_iterparameter). This issue is now fixed by using a new random seed for each warm start.
🚀 Travis CI now creates and uploads wheels for every new release.
🐧 We can now use
pip install fastFMon Linux and OSX (only 64bit).
🚀 This release makes fastFM Python3 compatible and greatly simplifies the build process on OSX and Linux.
🛠 Bugfix: calling als solver with rank=0 lead to memory error.
- ➕ Add Travis CI set-up (contributed by takuti)
- Python3 compatible (contributed by chezou)
- 👌 Support for older scikit-learn version (contributed by macks22)
- 👉 Makefile is now OSX compatible (contributed by altimin)
- ✂ Remove glib and argp dependencies from library.
- ✂ Remove last OSX dependency (cblas) from library (contributed by takuti)
- ⚡️ Update fastFM-core to v0.2.0
v0.1.1July 09, 2015
v0.1.0February 17, 2015