Releases: recommenders-team/recommenders
Releases · recommenders-team/recommenders
Recommenders 1.2.0
New algorithms or improvements
- Implemented Spark item to item recommenders by @ChuyangKe in #1809
- Correct packaging commands in SARPlus workflow by @simonzhaoms in #1860
- New URL of Glove from Huggingface by @miguelgfierro in #1949
- Bug in Deeprec tests and adding more tests by @miguelgfierro in #1957
- Make early_stopping a callable in LightGBM by @miguelgfierro in #1967
- Update Hybrid algo classification to align with Recommenders book and Aggarwal by @miguelgfierro in #2050
- Fixed bug when reading dataset with timestamp for sasrec model by @gazon1 in #2052
- Catch import error separately for SUMModel by @SimonYansenZhao in #2077
- Fixed error in fastai in nightly by @miguelgfierro in #2068
New utilities or improvements
- Optimized Python splitters by @ChuyangKe in #1802
- Replace append with pd.concat by @gro1m in #1811
- Python generalized ndcg by @ChuyangKe in #1812
- Simplify eval args by @AdityaSoni19031997 in #1828
- CVE-2007-4559 Patch by @TrellixVulnTeam in #1835
- New notebook executor #1865 #2048 #2031
- Restricting cornac to 1.15.1 for issue with 1.15.4 by @miguelgfierro in #1934
- Refactor ranking metric
mapto be the same as Spark's by @loomlike in #2004 - Correct MIND user behavior history construction by @thaiminhpv in #2054
- Merged two concats into one by @daviddavo in #2075
New notebooks or improvements
- Minor change in lightgcn_deep_dive.ipynb by @miguelgfierro in #1814
- Removed unused import by @miguelgfierro in #1824
- Benchmark movielens in #1831 #1846
- Fix error Wide and Deep by @miguelgfierro in #1854
- Update xDeepFM notebook and fix test error by @miguelgfierro in #1850
- Rerun and clean dataprep notebooks by @miguelgfierro in #1873
- typo fixes wrt notebook by @AdityaSoni19031997 in #1836
- Update multinomial_vae.py by @kone807 in #1916
- Review CPU notebooks in quick start with Python 3.9 by @miguelgfierro in #1944
- Rerun and clean notebooks #1947 #1950
- Update DKN notebook by @miguelgfierro in #1959
Other features
- Explicitly list references in the pull request template by @simonzhaoms in #1798
- Improve README.md in #1805 #1827 #1906 #1871 #1912 #2058 #2053
- Improve SETUP in #1920 #1926 #1923
- Miguel/remove ado by @miguelgfierro in #1820
- Optimize tests in #1823 #1819 #1808 #1837 #1907 #1911
- Refactor tests into new categories reviewed by Eric Gamma in #1989 #1822
- Remove pull_request_target by @miguelgfierro in #1840
- AzureML test improvements #1842 #1845 #1844 #1855 #1863 #1864 #1897 #1885 #2009 #1797 #2069 #2059
- Workflow dispatch for manually trigger SAR+ tests by @miguelgfierro in #1880
- Update the Python version support #1901 #1974 #1988 #1937
- Fix pyspark test bugs in #1909 #1899
- Fix GPU test bugs in #1886 #2046 #1995 #2045
- Fix CPU test bugs in #1879 #1882 #2033 #2037 #1797
- Remove deprecated utilities in #1917 #1935 #1982
- Remove non essential deps by @miguelgfierro in #1939 #1938 #1952 #1971
- Remove non essential files #1799 #1979 #1993 #2007 #2000
- Moving to the Linux Foundation #1970 #1977 #1978 #2003 #2008 #1976
- Typos #1984 #1866
- Merging the extra_requires examples into the core package by @miguelgfierro in #1987
- Security alerts and issues with Tensorflow in #2017 #2071 #2022
- New documentation with Jupyter book in #2051 #2078
- Fix issues with pandera by @anargyri in #2061 #2062
New Contributors
- @gro1m made their first contribution in #1811
- @TrellixVulnTeam made their first contribution in #1835
- @kone807 made their first contribution in #1916
- @henningsway made their first contribution in #1984
- @SimonYansenZhao made their first contribution in #1988
- @thaiminhpv made their first contribution in #2054
- @gazon1 made their first contribution in #2052
Full Changelog: 1.1.1...1.2.0
Contributors
henningsway, miguelgfierro, and 12 other contributors
Assets 4
Recommenders 1.1.1
New algorithms or improvements
- Reduce iterations of W&D to reduce the integration tests time in #1698
- Implementation of most frequent recommendation in #1666
- Implement time_now for sarplus in #1719 #1721
- Add a fast failure in SAR+ if the similarity metric is not within the options in #1743
- SAR item similarity dtype correction in #1751
- Simplify SAR test data loading functions in #1752
- Reformat SAR+ SQL queries in #1772
- Add new item similarity metrics for SAR in #1754
New utilities or improvements
- Rewrite get_top_k_items() to improve runtime in #1748
- Optimized Spark recall_at_k time performance in #1796
New notebooks or improvements
- Fix missing import in FastAI notebook #1708
- Review NCF notebook in #1703 #1712
- Review LigthFM notebook and add test in #1706
- Review BPR notebook in #1704
- Review LightGCN notebook in #1714
- Review DKN notebook in #1722
- Review SAR notebook #1738 #1768
Other features
- Enable distributed tests with AzureML #1696 #1717 #1729 #1733 #1739 #1747 #1732 #1755 #1763 #1771 #1773 #1775 #1787 #1788 #1794
- Added tests for Python 3.8 and 3.9 in #1756
- Image of contributors in #1692
- Update README.md in #1709 #1711 #1767
- Error in codeowners file in #1699
- Add test to check if CuDNN is enabled in #1715
- Update docker image reference to internal registry in #1727
- Fixed a link error in data_transform.ipynb in #1736
- Added tests for ranking function get_top_k_items() in #1757
- Fix memory error in CPU nightly workflow in #1759
- Update test infrastructure explanation #1776 #1777
- Added time performance tests in #1765
- Add path filter to avoid triggering unit tests when we change a markdown in #1791
Full Changelog: 1.1.0...1.1.1
Recommenders 1.1.0
New algorithms or improvements
- SASRec and SSEPT in Tensorflow 2.x in #1530 #1621 #1678
- RBM Code Cleanup, model save and other additions in #1599 #1618 #1622
- Overwrite older test file in NCF deep dive to avoid bug in #1674
- SAR+ improvement and bug fixes #1636 #1644 #1680 #1671
- NCF improvement and bug fixes in #1612
- Remove drop_duplicates() from SAR method fix #1464 in #1588
- SAR literal fix in #1663
New utilities or improvements
- Update lightfm_utils.py in #1624
- Change formats of user_ids and item_ids arg. in LigthFM in #1651
- Fix randomness issue in spark_stratified_split() in #1654
- Clarification for jaccard and lift similarity measures in #1668
- Use numpy divide in explained variance in #1691
- Change MovieLens URL from HTTP to HTTPS in #1677
- Remove casting of user and item IDs in Spark evaluation in #1686
- Persist intermediate data to avoid non-determinism caused by Spark lazy random evaluation in #1676 #1652
New notebooks or improvements
- Fix notebook build failure on Spark 3.2 in #1608
- Remove early stopping round from LightGBM example notebook in #1620
Other features
- Enable Python 3.8 and 3.9 in #1626 #1617
- Upgrade Python from 3.6 to 3.7 in ADO tests pipeline in #1627
- Increase time out for GPU nightly tests in #1623
- Lower LightGBM test AUC base value in #1619
- Change timeouts for tests #1625 #1661 #1684
- Scenario gaming in #1637
- Limiting tests: reducing the time of the news recommendation GPU notebooks in #1656
- Remove pydocumentdb in install_requires in #1629
- Change and improve dependencies #1630 #1653
- Fix Spark tuning test in #1635
- Typos in markdown files and other files #1639 #1589 #1646 #1647 #1688
- Update Dockerfile in #1645
- Improve documentation #1648 #1669 #1682 #1690 #1672
- Codecov Fix in #1665
- Set Spark env variables in nightly test in #1655 #1659
Full Changelog: 1.0.0...1.1.0
Recommenders 1.0.0
Backwards incompatible changes
New algorithms or improvements
- Improve algos visibility #1542
- LightGBM test improvement #1531
- Fix Surprise and Python 3.7 #1540
- TF-IDF runtime enhancement changes #1571
- Add Spark 3.x support for SARplus #1566
New utilities or improvements
- Upgrade to Spark v3 #1555 , #1549 , #1543
- Move scikit-surprise and pymanopt from setup.py #1602
- Issue with pymanopt #1606
New notebooks or improvements
- Fix bugs in RBM notebooks #1581
- Remove explicit mapping of ratings to integers from RBM notebooks #1585
Other features
- Fix nightly workflows #1576 , #1548
- Stabilize more flaky tests #1558
- Miscellaneous Pipeline Fixes #1545
- Optimize Notebook Unit Tests #1538
- Development status change to production/stable #1579
- Update dependencies #1569, #1570
- Fix Databricks installation script #1531
- Adding codespace deployment #1521
- Improve GitHub tests #1518, #1578, #1590, #1592
- Flake8 Fixes #1552 , #1550
- Improvement in documentation #1591, #1598, #1594, #1603
- Update release pipeline #1596
Recommenders 0.7.0
Backwards incompatible changes
New algorithms or improvements
- Missing import in VAE #1508
New utilities or improvements
retryingimport #1487- Addition of diversity, novelty, coverage and serendipity metrics #1536, #1535, #1522, #1505, #1491, #1470, #1465
New notebooks or improvements
- New notebook showcasing diversity, novelty, coverage, and serendipity metrics in Spark #1488, #1470, #1465
Other features
- Enablement of LightGBM version 3 #1527
- Enablement of all Python 3.7 micro versions #1474
- Installation in
virtualenvandvenv#1520, #1476 - Installation from PyPI in docker container #1509
- Read the Docs builds #1529, #1528
- Documentation improvements #1515, #1469, #1462
- CI pipelines on GitHub workflows (WIP) #1517, #1503, #1499, #1494, #1490
Recommenders 0.6.0
New utilities or improvements
- Fix URL in unit tests #1447
- Improve documentation #1446 #1440 #1436 #1428 #1426 #1425 #1415
- Add retry to maybe_downlad function #1427
New notebooks or improvements
- Notebook for diversity metrics #1416
- Update evaluation notebook with new diversity metrics #1416
- Fix xlearn notebook #1427
Other features
Recommenders 0.5.0
Repo structure
New dataset and competition support
- Microsoft News dataset (MIND) and Microsoft News Recommendation Challenge #1247 #1236
New algorithms or improvements
- Optimize GPU usage of news recommendation algorithms #1235
- Optimize surprise utilities #1224
- GeoIMC algorithm #1204
- Standard VAE algorithm #1194
- Multinomial VAE algorithm #1194
New utilities or improvements
- Operationalization example for sequential models #1254
- Fix bug with fastai #1288
- Fix bug in affinity matrix #1243
- Fix conflict with MMLSpark version #1230
- Fix negative feedback smapler #1200
New notebooks or improvements
- Update AzureML Designer notebooks #1286 #1253
- KDD2020 tutorial: paper recommendation with Microsoft Academic Graph #1208
- Update o16n notebook for real time scoring #1176
- Reduce verbosity on tensorflow notebooks #1276
Other features
Recommenders 0.4.0
New algorithms or improvements
- DKN fix #1165
- GeoIMC #1142
- LSTUR #1137 #1080
- NAML #1137 #1080
- NPA #1137 #1080
- NRMS #1137 #1080
- LighGCN #1130 #1123
- NextItNet #1130 #1126
- Fix SAR #1128 #1023 #1018 #991
- LightFM #1096
- TFIDF recommender #1088
- A2SVD #1010
- GRU4Rec #1010
- Caser #1010
- SLi-Rec #1010
- SARplus #955
- BPR with cornac library #950 #944 #937
New utilities or improvements
- MIND dataset #1153
- Fix Text iterator #1133
- Fix NNI utils #1131
- Azure Designer dependencies #1115 #1101 #1095 #1077 #1060
- Fix tests #1057 #1004 #954 #935 #932
New notebooks or improvements
- DKN notebook with MIND dataset #1165 #1137
- GeoIMC notebook #1142
- LSTUR notebook #1137 #1080
- NAML notebook #1137 #1080
- NPA notebook #1137 #1080
- NRMS notebook #1137 #1080
- LighGCN notebook #1130 #1123
- NextItNet notebook #1130 #1126
- Implementation of Recommenders into Azure Designer #1115 #1101 #1095 #1060 #1036
- NCF hyperparameter tunning notebook #1102 #1092
- LightFM notebook #1096
- TFIDF recommender notebook #1088
- Add timer class into notebooks 1063
- Fix xlearn notebook #1006 #974
- o16n notebook fix #1003 #969
- A2SVD notebook #1010
- GRU4Rec notebook #1010
- Caser notebook #1010
- SLi-Rec notebook #1010
- BPR with cornac notebook #950 #944 #937
Other features
Recommenders 0.3.1
New algorithms or improvements
New utilities or improvements
- Fixed bug in python evaluator #863
- Updated nni version and utils #856
- Updated sum check #874
- Changed url download util to use requests #813
New notebooks or improvements
- Optimized spark notebooks #864
- New notebook on knowledge graph generation with wikidata #881 #902
- Wide-deep hyperdrive notebook AzureML API update #847
Other features
- Added Docker support (Docker file) for all of the three (CPU/GPU/Spark) environment
- Added setup.py for pip installation #851
- Added sphinx documentation #859
- Published documentation on readthedocs #912
- Fixed spark testing issues #850
- Added tests with AzureML compute target #848 #846 #839 #823
- Development of Xamarin app for movies recommendation using Recommenders engine https://github.com/microsoft/recommenders_engine_example_layout
Recommenders 0.3.0
New platform support
New algorithms or improvements
- LightGBM #633 #735
- RLRMC #729
- Changed seed for GPU algos for reproducibility #785 #748
- Added benchmark #715
- Fixed bugs in SAR #697 #619
New utilities or improvements
- Python evaluation improvement by memoization #713
- Improved tests #706
- New algos for hyperparameter tuning with NNI #687
- Criteo dataloader #642
- Wrapper VW #592
- Added more data formats #605
- New metrics #580
New notebooks or improvements
- SAR remote execution through AzureML #728
- SAR remote execution of notebook through AzureML #681
- LightGBM with small criteo on CPU #633
- LightGBM o16n on Databricks with MMLSpark #735 #714 #682 #680
- Hyperparameter tuning with NNI on Surprise SVD #687
- Hyperparameter tuning with Hyperdrive #546
Other features
- Fixed bugs in utilities, tests and notebooks
- New unit, smoke and integration tests for the new algos