‘Lazy Predict’ Tutorial for AutoML with scikit-learn [Eryk Lewinson]
Eryk Lewinson wrote a tutorial on how to use Lazy Predict, which is an automated machine learning (AutoML) extension by Shankar Rao Pandala for scikit-learn....
Category: Software Libraries & APIs
Recommender-Systems Version Control: TensorFlow releases ‘Machine Learning Metadata (MLMD)’
Version control for recommender systems is a topic that should receive more attention in the community. Given that TensorFlow is often used for implementing recommender...
‘AutoGL’, a new AutoML framework for Graphs by Tsinghua University
‘Graphs’ and linked data are highly useful in generating effective recommender systems. Also in machine learning, graphs have gained popularity. Now, researchers from Tsinghua University...
HetSeq: Training BERT on a random assortment of GPUs [Yifan Ding et al.]
BERT has brought huge changes to how NLP is done, and also had a notable impact on recommender systems (not always though*). However, training BERT...
LinkedIn introduces “GDMix”, a deep ranking personalization framework
Jun Shi from LinkedIn announced the release of GDMix (GitHub), a deep ranking personalization framework. GDMix stands for Generalized Deep Mixed Model and is… a solution...
TensorFlow introduces ‘TensorFlow Recommenders’ (TFRS)
This is big news for the recommender-system community: Maciej Kula and James Chen from Google Brain announce TensorFlow Recommenders (TFRS), an official recommender-systems package for...
Oracle announces Tribuo, a Java machine-learning library [Adam Pocock @ Oracle]
Adam Pocock from Oracle announced the public release of Oracle’s so-far in-house machine-learning library Tribuo. The library is not specifically designed for recommender-systems. Yet, it...
TensorFlow introduces a new ‘end-to-end’ solution for on-device recommendations with TFLite
Ellie Zhou, Tian Lin, Cong Li, Shuangfeng Li, and Sushant Prakash from TensorFlow announced in a blog post that they open-source an end-to-end solution for...
Scalable Recommender Systems with NVTabular- A Fast Tabular Data Loading and Transformation Library [Ronay Ak @ Medium]
Ronay Ak et al. from RapidsAI wrote a nice in-depth post on how to use NVIDIA´s NVTabular to develop a recommender system that works with...
Building Personal Recommender Systems with Milvus and PaddlePaddle [Milvus@Medium]
In this article we use PaddlePaddle, a deep learning platform from Baidu, to build a model and combine Milvus, a vector similarity search engine, to...