https://github.com/recommenders-team/recommenders - Recommenders 1.2.1

New algorithms or improvements

• SAR sparse multiplication modification due to a breaking change in scipy by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/2083
• Remove LightFM from core package in #2122 #2144
• Modified 2 files to update newsrec model by @sumana-2705 in https://github.com/recommenders-team/recommenders/pull/2125

New utilities or improvements

• Flattening matrix so dataframe can be built correctly by @gramhagen in https://github.com/recommenders-team/recommenders/pull/2084
• Added r-precision by @daviddavo in https://github.com/recommenders-team/recommenders/pull/2086
• Fix breaking change in sklearn in log_loss by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/2106
• Fix and improve ImplicitCF by @daviddavo in #2117 #2164
• Changing Function Name to reflect new Tensorflow interface. by @siyerp in https://github.com/recommenders-team/recommenders/pull/2143
• Deprecated use of dict in SeriesGroupBy.agg by @daviddavo in https://github.com/recommenders-team/recommenders/pull/2114
• Revert and fix python evaluation by @daviddavo in https://github.com/recommenders-team/recommenders/pull/2119
• Updated function signatures to comply with new tensorflow requirements by @siyerp in https://github.com/recommenders-team/recommenders/pull/2146
• Update MIND dataset utilities by @miguelgfierro in #2145 #2155 #2160

New notebooks or improvements

• Update jupyter dep to accomodate Colab by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/2108
• Update cornacbivaedeep_dive.ipynb: fix typos by @martin0258 in https://github.com/recommenders-team/recommenders/pull/2104
• Correct variable used in pickle dump in mind_utils.ipynb by @ubergonmx in https://github.com/recommenders-team/recommenders/pull/2158

Other features

• Fix issues with numpy by @daviddavo in #2113 #2120
• Update setup instructions #2080 #2181
• Added ideas and guidelines for new contributors by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/2103
• Set scipy <= 1.13.1 by @SimonYansenZhao in https://github.com/recommenders-team/recommenders/pull/2127
• Added free course on Recommendation systems by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/2135
• Add reference to scenarios to README.md by @anargyri in https://github.com/recommenders-team/recommenders/pull/2093
• Documentation improvement and typos #2102 #2109 #2096 #2130
• Updated Issue Template with "Willingness to Contribute" Section for issue #2032 by @sumana-2705 in https://github.com/recommenders-team/recommenders/pull/2123
• Moved pymanopt tests to experimental test group #2138 by @daviddavo in https://github.com/recommenders-team/recommenders/pull/2139
• Migrate AML SDK from v1 to v2 by @SimonYansenZhao in https://github.com/recommenders-team/recommenders/pull/2134
• Update dev container by @SimonYansenZhao in https://github.com/recommenders-team/recommenders/pull/2157
• Improve GitHub actions #2159 #2190 #2197
• Update service principal role to AzureML Compute Operator for improved security by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/2169
• Update the code of conduct by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/2177
• Use managed identity with OpenID Connect for Azure login by @SimonYansenZhao in https://github.com/recommenders-team/recommenders/pull/2182
• Merge multiple Dockerfiles into a single one by @SimonYansenZhao in https://github.com/recommenders-team/recommenders/pull/2167
• Install sbt for sarplus tests by @SimonYansenZhao in https://github.com/recommenders-team/recommenders/pull/2192

New Contributors

• @martin0258 made their first contribution in https://github.com/recommenders-team/recommenders/pull/2104
• @Kingston257 made their first contribution in https://github.com/recommenders-team/recommenders/pull/2109
• @sumana-2705 made their first contribution in https://github.com/recommenders-team/recommenders/pull/2123
• @siyerp made their first contribution in https://github.com/recommenders-team/recommenders/pull/2143
• @ubergonmx made their first contribution in https://github.com/recommenders-team/recommenders/pull/2158
• @ved93 made their first contribution in https://github.com/recommenders-team/recommenders/pull/2181

Full Changelog: https://github.com/recommenders-team/recommenders/compare/1.2.0...1.2.1

- Python
Published by github-actions[bot] over 1 year ago

https://github.com/recommenders-team/recommenders - Recommenders 1.2.0

New algorithms or improvements

• Implemented Spark item to item recommenders by @ChuyangKe in https://github.com/recommenders-team/recommenders/pull/1809
• Correct packaging commands in SARPlus workflow by @simonzhaoms in https://github.com/recommenders-team/recommenders/pull/1860
• New URL of Glove from Huggingface by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1949
• Bug in Deeprec tests and adding more tests by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1957
• Make early_stopping a callable in LightGBM by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1967
• Update Hybrid algo classification to align with Recommenders book and Aggarwal by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/2050
• Fixed bug when reading dataset with timestamp for sasrec model by @gazon1 in https://github.com/recommenders-team/recommenders/pull/2052
• Catch import error separately for SUMModel by @SimonYansenZhao in https://github.com/recommenders-team/recommenders/pull/2077
• Fixed error in fastai in nightly by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/2068

New utilities or improvements

• Optimized Python splitters by @ChuyangKe in https://github.com/recommenders-team/recommenders/pull/1802
• Replace append with pd.concat by @gro1m in https://github.com/recommenders-team/recommenders/pull/1811
• Python generalized ndcg by @ChuyangKe in https://github.com/recommenders-team/recommenders/pull/1812
• Simplify eval args by @AdityaSoni19031997 in https://github.com/recommenders-team/recommenders/pull/1828
• CVE-2007-4559 Patch by @TrellixVulnTeam in https://github.com/recommenders-team/recommenders/pull/1835
• New notebook executor #1865 #2048 #2031
• Restricting cornac to 1.15.1 for issue with 1.15.4 by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1934
• Refactor ranking metric map to be the same as Spark's by @loomlike in https://github.com/recommenders-team/recommenders/pull/2004
• Correct MIND user behavior history construction by @thaiminhpv in https://github.com/recommenders-team/recommenders/pull/2054
• Merged two concats into one by @daviddavo in https://github.com/recommenders-team/recommenders/pull/2075

New notebooks or improvements

• Minor change in lightgcndeepdive.ipynb by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1814
• Removed unused import by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1824
• Benchmark movielens in https://github.com/recommenders-team/recommenders/pull/1831 #1846
• Fix error Wide and Deep by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1854
• Update xDeepFM notebook and fix test error by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1850
• Rerun and clean dataprep notebooks by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1873
• typo fixes wrt notebook by @AdityaSoni19031997 in https://github.com/recommenders-team/recommenders/pull/1836
• Update multinomial_vae.py by @kone807 in https://github.com/recommenders-team/recommenders/pull/1916
• Review CPU notebooks in quick start with Python 3.9 by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1944
• Rerun and clean notebooks https://github.com/recommenders-team/recommenders/pull/1947 #1950
• Update DKN notebook by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1959

Other features

• Explicitly list references in the pull request template by @simonzhaoms in https://github.com/recommenders-team/recommenders/pull/1798
• Improve README.md in https://github.com/recommenders-team/recommenders/pull/1805 #1827 #1906 #1871 #1912 #2058 #2053
• Improve SETUP in https://github.com/recommenders-team/recommenders/pull/1920 #1926 #1923
• Miguel/remove ado by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/1820
• Optimize tests in https://github.com/recommenders-team/recommenders/pull/1823 #1819 #1808 #1837 #1907 #1911
• Refactor tests into new categories reviewed by Eric Gamma in https://github.com/recommenders-team/recommenders/pull/1989 #1822
• Remove pullrequesttarget by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/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 https://github.com/recommenders-team/recommenders/pull/1880
• Update the Python version support #1901 #1974 #1988 #1937
• Fix pyspark test bugs in https://github.com/recommenders-team/recommenders/pull/1909 #1899
• Fix GPU test bugs in https://github.com/recommenders-team/recommenders/pull/1886 #2046 #1995 #2045
• Fix CPU test bugs in https://github.com/recommenders-team/recommenders/pull/1879 #1882 #2033 #2037 #1797
• Remove deprecated utilities in https://github.com/recommenders-team/recommenders/pull/1917 #1935 #1982
• Remove non essential deps by @miguelgfierro in https://github.com/recommenders-team/recommenders/pull/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 https://github.com/recommenders-team/recommenders/pull/1987
• Security alerts and issues with Tensorflow in https://github.com/recommenders-team/recommenders/pull/2017 #2071 #2022
• New documentation with Jupyter book in https://github.com/recommenders-team/recommenders/pull/2051 #2078
• Fix issues with pandera by @anargyri in https://github.com/recommenders-team/recommenders/pull/2061 #2062

New Contributors

• @gro1m made their first contribution in https://github.com/recommenders-team/recommenders/pull/1811
• @TrellixVulnTeam made their first contribution in https://github.com/recommenders-team/recommenders/pull/1835
• @kone807 made their first contribution in https://github.com/recommenders-team/recommenders/pull/1916
• @henningsway made their first contribution in https://github.com/recommenders-team/recommenders/pull/1984
• @SimonYansenZhao made their first contribution in https://github.com/recommenders-team/recommenders/pull/1988
• @thaiminhpv made their first contribution in https://github.com/recommenders-team/recommenders/pull/2054
• @gazon1 made their first contribution in https://github.com/recommenders-team/recommenders/pull/2052

Full Changelog: https://github.com/recommenders-team/recommenders/compare/1.1.1...1.2.0

- Python
Published by github-actions[bot] about 2 years ago

https://github.com/recommenders-team/recommenders - Recommenders 1.1.1

New algorithms or improvements

• Reduce iterations of W&D to reduce the integration tests time in https://github.com/microsoft/recommenders/pull/1698
• Implementation of most frequent recommendation in https://github.com/microsoft/recommenders/pull/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 https://github.com/microsoft/recommenders/pull/1743
• SAR item similarity dtype correction in https://github.com/microsoft/recommenders/pull/1751
• Simplify SAR test data loading functions in https://github.com/microsoft/recommenders/pull/1752
• Reformat SAR+ SQL queries in https://github.com/microsoft/recommenders/pull/1772
• Add new item similarity metrics for SAR in https://github.com/microsoft/recommenders/pull/1754

New utilities or improvements

• Rewrite gettopk_items() to improve runtime in https://github.com/microsoft/recommenders/pull/1748
• Optimized Spark recallatk time performance in https://github.com/microsoft/recommenders/pull/1796

New notebooks or improvements

• Fix missing import in FastAI notebook https://github.com/microsoft/recommenders/pull/1708
• Review NCF notebook in #1703 #1712
• Review LigthFM notebook and add test in https://github.com/microsoft/recommenders/pull/1706
• Review BPR notebook in https://github.com/microsoft/recommenders/pull/1704
• Review LightGCN notebook in https://github.com/microsoft/recommenders/pull/1714
• Review DKN notebook in https://github.com/microsoft/recommenders/pull/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 https://github.com/microsoft/recommenders/pull/1756
• Image of contributors in https://github.com/microsoft/recommenders/pull/1692
• Update README.md in #1709 #1711 #1767
• Error in codeowners file in https://github.com/microsoft/recommenders/pull/1699
• Add test to check if CuDNN is enabled in https://github.com/microsoft/recommenders/pull/1715
• Update docker image reference to internal registry in https://github.com/microsoft/recommenders/pull/1727
• Fixed a link error in data_transform.ipynb in https://github.com/microsoft/recommenders/pull/1736
• Added tests for ranking function gettopk_items() in https://github.com/microsoft/recommenders/pull/1757
• Fix memory error in CPU nightly workflow in https://github.com/microsoft/recommenders/pull/1759
• Update test infrastructure explanation #1776 #1777
• Added time performance tests in https://github.com/microsoft/recommenders/pull/1765
• Add path filter to avoid triggering unit tests when we change a markdown in https://github.com/microsoft/recommenders/pull/1791

Full Changelog: https://github.com/microsoft/recommenders/compare/1.1.0...1.1.1

- Python
Published by github-actions[bot] about 4 years ago

https://github.com/recommenders-team/recommenders - Recommenders 1.1.0

New algorithms or improvements

• SASRec and SSEPT in Tensorflow 2.x in https://github.com/microsoft/recommenders/pull/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 https://github.com/microsoft/recommenders/pull/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 https://github.com/microsoft/recommenders/pull/1588
• SAR literal fix in https://github.com/microsoft/recommenders/pull/1663

New utilities or improvements

• Update lightfm_utils.py in https://github.com/microsoft/recommenders/pull/1624
• Change formats of userids and itemids arg. in LigthFM in https://github.com/microsoft/recommenders/pull/1651
• Fix randomness issue in sparkstratifiedsplit() in https://github.com/microsoft/recommenders/pull/1654
• Clarification for jaccard and lift similarity measures in https://github.com/microsoft/recommenders/pull/1668
• Use numpy divide in explained variance in https://github.com/microsoft/recommenders/pull/1691
• Change MovieLens URL from HTTP to HTTPS in https://github.com/microsoft/recommenders/pull/1677
• Remove casting of user and item IDs in Spark evaluation in https://github.com/microsoft/recommenders/pull/1686
• Persist intermediate data to avoid non-determinism caused by Spark lazy random evaluation in https://github.com/microsoft/recommenders/pull/1676 #1652

New notebooks or improvements

• Fix notebook build failure on Spark 3.2 in https://github.com/microsoft/recommenders/pull/1608
• Remove early stopping round from LightGBM example notebook in https://github.com/microsoft/recommenders/pull/1620

Other features

• Enable Python 3.8 and 3.9 in https://github.com/microsoft/recommenders/pull/1626 #1617
• Upgrade Python from 3.6 to 3.7 in ADO tests pipeline in https://github.com/microsoft/recommenders/pull/1627
• Increase time out for GPU nightly tests in https://github.com/microsoft/recommenders/pull/1623
• Lower LightGBM test AUC base value in https://github.com/microsoft/recommenders/pull/1619
• Change timeouts for tests #1625 #1661 #1684
• Scenario gaming in https://github.com/microsoft/recommenders/pull/1637
• Limiting tests: reducing the time of the news recommendation GPU notebooks in https://github.com/microsoft/recommenders/pull/1656
• Remove pydocumentdb in install_requires in https://github.com/microsoft/recommenders/pull/1629
• Change and improve dependencies #1630 #1653
• Fix Spark tuning test in https://github.com/microsoft/recommenders/pull/1635
• Typos in markdown files and other files #1639 #1589 #1646 #1647 #1688
• Update Dockerfile in https://github.com/microsoft/recommenders/pull/1645
• Improve documentation #1648 #1669 #1682 #1690 #1672
• Codecov Fix in https://github.com/microsoft/recommenders/pull/1665
• Set Spark env variables in nightly test in https://github.com/microsoft/recommenders/pull/1655 #1659

Full Changelog: https://github.com/microsoft/recommenders/compare/1.0.0...1.1.0

- Python
Published by miguelgfierro over 4 years ago

https://github.com/recommenders-team/recommenders - Recommenders 1.0.0

Backwards incompatible changes

• TensorFlow upgrade to 2.6.1 / 2.7 #1574 , #1565 , #1540

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

- Python
Published by miguelgfierro over 4 years ago

https://github.com/recommenders-team/recommenders - Recommenders 0.7.0

Backwards incompatible changes

• Renaming of folders #1485, #1478
• Change of the PyPI package name to recommenders #1477

New algorithms or improvements

• Missing import in VAE #1508

New utilities or improvements

• retrying import #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 virtualenv and venv #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

- Python
Published by miguelgfierro almost 5 years ago

https://github.com/recommenders-team/recommenders - 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

• Generate package for PyPi #1445 #1442 #1441 #1429
• Improve installation process #1455 #1431
• Fix tests #1452 #1427
• Generate pipeline for release #1427

- Python
Published by miguelgfierro about 5 years ago

https://github.com/recommenders-team/recommenders - Recommenders 0.5.0

Repo structure

• Default branch renamed from master to main #1284 #1278

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

• Upgrade papermill and scrapbook for testing #1271 #1270 #1282 #1289
• Fix tests #1244 #1242 #1226 #1218
• Fix issue with spark installation #1186
• Update python version #1202
• Notice for java dependency #1209
• Reactivate CICD pipelines #1284

- Python
Published by miguelgfierro about 5 years ago

https://github.com/recommenders-team/recommenders - Recommenders 0.4.0

New algorithms or improvements

• DKN fix https://github.com/microsoft/recommenders/pull/1165
• GeoIMC https://github.com/microsoft/recommenders/pull/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 https://github.com/microsoft/recommenders/pull/1153
• Fix Text iterator https://github.com/microsoft/recommenders/pull/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 https://github.com/microsoft/recommenders/pull/1165 https://github.com/microsoft/recommenders/pull/1137
• GeoIMC notebook https://github.com/microsoft/recommenders/pull/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

• Fix installation on Databricks https://github.com/microsoft/recommenders/pull/1161 #965
• Fix docker https://github.com/microsoft/recommenders/pull/1146 #1120 #1070 #1058 #1034
• Fix Azure blob version #1119
• Pin TensorFlow #1098
• Code structure refactor #1086
• Business scenarios and glossary #1086
• ADO artifact #1069
• Avoid pandas>1 #1052
• CICD #1002 #998 #994 #980

- Python
Published by miguelgfierro about 5 years ago

https://github.com/recommenders-team/recommenders - Recommenders 0.3.1

New algorithms or improvements

• Improved SAR performance #914 #922
• Utils for wikidata knowledge graph #881 #902

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/recommendersengineexample_layout

- Python
Published by miguelgfierro about 5 years ago

https://github.com/recommenders-team/recommenders - Recommenders 0.3.0

New platform support

• Windows support with tests #797 #726

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

- Python
Published by miguelgfierro about 5 years ago

https://github.com/recommenders-team/recommenders - Recommenders 0.2.0

New Algorithms or improvements

• Vowpal Wabbit (VW) https://github.com/Microsoft/Recommenders/pull/452
• xDeepFM https://github.com/Microsoft/Recommenders/pull/453
• DKN https://github.com/Microsoft/Recommenders/pull/453
• NCF https://github.com/Microsoft/Recommenders/pull/392
• RBM https://github.com/Microsoft/Recommenders/pull/390
• FastAI Embedding dot Bias https://github.com/Microsoft/Recommenders/pull/411
• Optimization of SAR

New utilities or improvements

• Improved the performance of python splitters https://github.com/Microsoft/Recommenders/pull/517
• Added GPU utilities
• Added utilities for hyperparameter tuning

New Notebooks or improvements

• Improved o16n notebook with ALS, Movielens and Databricks https://github.com/Microsoft/Recommenders/pull/475
• Added a deep dive notebook on VW https://github.com/Microsoft/Recommenders/pull/452
• Improved notebook for hyperparameter tuning on Spark https://github.com/Microsoft/Recommenders/pull/444
• New notebook on FastAI Embedding dot Bias algo https://github.com/Microsoft/Recommenders/pull/411
• New notebook of deep dive on NCF https://github.com/Microsoft/Recommenders/pull/392
• New quick start notebook of RBM https://github.com/Microsoft/Recommenders/pull/390
• New deep dive notebook of RBM https://github.com/Microsoft/Recommenders/pull/390
• New quickstart notebook of xDeepFM with synthetic data
• New quickstart notebook of DKN with synthetic data
• New notebook on data transformation https://github.com/Microsoft/Recommenders/pull/384

Other features

• Fixed bugs in utilities, tests and notebooks
• Added an installation script for Databricks https://github.com/Microsoft/Recommenders/pull/457
• Changed installer from a bash to a python script https://github.com/Microsoft/Recommenders/pull/512
• Added a parameter to control pyspark version in the installer https://github.com/Microsoft/Recommenders/pull/461
• Optimized tests to be quicker https://github.com/Microsoft/Recommenders/pull/486
• New unit, smoke and integration tests for the new algos
• Added GPU test pipeline https://github.com/Microsoft/Recommenders/pull/408
• Improved Github metrics tracker https://github.com/Microsoft/Recommenders/pull/400

- Python
Published by miguelgfierro about 5 years ago

https://github.com/recommenders-team/recommenders - Recommenders 0.1.1

New Algorithms or improvements

• Improved SAR single node for top k recommendations. User can decide if the recommended top k items to be sorted or not.

New utilities or improvements

• Added data related utility functions like movielens data download in Python and PySpark.
• Added new data split method (timestamp based split) added.

New Notebooks or improvements

• Added an O16N notebook for Spark ALS movie recommender on Azure production services such as Databricks, Cosmos DB, and Kubernetes Services.
• Added SAR deep dive notebook with single-node implementation demonstrated.
• Added Surprise SVD deep dive notebook.
• Added Surprise SVD integration test.
• Added Surprise SVD ranking metrics evaluation.
• Made quick-start notebooks consistent in terms of running settings, i.e., experiment protocols (e.g., data split, evaluation metrics, etc.) and algorithm parameters (e.g., hyper parameters, remove seen items, etc.).
• Added a comparison notebook for easy benchmarking different algorithms.

Other features

• Updated SETUP with Azure Databricks.
• Added SETUP troubleshooting for Azure DSVM and Databricks.
• Updated READMEs under each notebook directory to provide comprehensive guidelines.
• Added smoke/integration tests on large movielens dataset (10mil and 20mil).
• Updated the Spark settings of CI/CD machine to eliminate unexpected build failures such as "no space left issue".

- Python
Published by yueguoguo over 7 years ago

https://github.com/recommenders-team/recommenders - Recommenders 0.1.0

New Algorithms or improvements

Development of SAR algorithm on three implementations: * SAR single node * SAR PySpark * SAR+

New utilities or improvements

• Dataset splitters in Python and PySpark.
• Rating and ranking metrics in Python and PySpark.

New Notebooks or improvements

• ALS quickstart with Movielens
• SAR single node quickstart with Movielens
• SAR PySpark quickstart with Movielens
• SAR+ quickstart with Movielens
• Data splitter
• ALS deep dive
• SAR deep dive
• Evaluation

Other features

• Benchmark of the current algorithms.
• Unit, smoke and integration tests for Python and PySpark environments.

- Python
Published by miguelgfierro over 7 years ago