- Movie Recommendations with Spark Collaborative Filtering - Dec 1, 2021.
Not sure what movie to watch? Ask your recommender system.
Apache Spark, Collaborative, Knime, Low-Code, Recommender Systems
- Inside recommendations: how a recommender system recommends - Nov 17, 2021.
We describe types of recommender systems, more specifically, algorithms and methods for content-based systems, collaborative filtering, and hybrid systems.
Recommendation Engine, Recommender Systems
- Enhancing Machine Learning Personalization through Variety - Aug 19, 2021.
Personalization drives growth and is a touchstone of good customer experience. Personalization driven through machine learning can enable companies to improve this experience while improving ROI for marketing campaigns. However, challenges exist in these techniques for when personalization makes sense and how and when specific options are recommended.
Machine Learning, Personalization, Recommender Systems
- Similarity Search: Euclid of Alexandria goes shoe shopping - Jun 2, 2021.
Many applications can be improved with similarity search. Similarity search can provide more relevant results and therefore improve business outcomes such as conversion rates, engagement rates, detected threats, data quality, and customer satisfaction.
Neural Networks, Pinecone, Recommender Systems, Search
- Deep Learning Recommendation Models (DLRM): A Deep Dive - Apr 9, 2021.
The currency in the 21st century is no longer just data. It's the attention of people. This deep dive article presents the architecture and deployment issues experienced with the deep learning recommendation model, DLRM, which was open-sourced by Facebook in March 2019.
Deep Learning, Recommendations, Recommender Systems
How LinkedIn Uses Machine Learning in its Recruiter Recommendation Systems - Oct 8, 2020.
LinkedIn uses some very innovative machine learning techniques to optimize candidate recommendations.
LinkedIn, Machine Learning, Recommendation Engine, Recommender Systems, Recruitment
- Content-Based Recommendation System using Word Embeddings - Aug 14, 2020.
This article explores how average Word2Vec and TF-IDF Word2Vec can be used to build a recommendation engine.
NLP, Recommendation Engine, Recommender Systems, TF-IDF, Word Embeddings, word2vec
- Building a Content-Based Book Recommendation Engine - Jul 28, 2020.
In this blog, we will see how we can build a simple content-based recommender system using Goodreads data.
Python, Recommendation Engine, Recommender Systems
- Recommender Systems in a Nutshell - Jul 23, 2020.
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about recommender systems and the ways they are used.
Interview, Recommendation Engine, Recommender Systems
- Recommender System Metrics: Comparing Apples, Oranges and Bananas - Feb 11, 2020.
This article will discuss a sometimes-overlooked aspect of what distinguishes recommender systems from other machine learning tasks: added uncertainties of measuring them.
Metrics, Recommendation Engine, Recommender Systems
- Content-based Recommender Using Natural Language Processing (NLP) - Nov 26, 2019.
A guide to build a content-based movie recommender model based on NLP.
Movies, Netflix, NLP, Python, Recommender Systems
How YouTube is Recommending Your Next Video - Oct 21, 2019.
If you are interested in learning more about the latest Youtube recommendation algorithm paper, read this post for details on its approach and improvements.
Recommendation Engine, Recommender Systems, Video, Youtube
- An Easy Introduction to Machine Learning Recommender Systems - Sep 4, 2019.
Recommender systems are an important class of machine learning algorithms that offer "relevant" suggestions to users. Categorized as either collaborative filtering or a content-based system, check out how these approaches work along with implementations to follow from example code.
Beginners, Machine Learning, Python, Recommendation Engine, Recommender Systems
- Order Matters: Alibaba’s Transformer-based Recommender System - Aug 23, 2019.
Alibaba, the largest e-commerce platform in China, is a powerhouse not only when it comes to e-commerce, but also when it comes to recommender systems research. Their latest paper, Behaviour Sequence Transformer for E-commerce Recommendation in Alibaba, is yet another publication that pushes the state of the art in recommender systems.
Alibaba, Recommendation Engine, Recommender Systems, Transformer
How Data Science Is Used Within the Film Industry - Jul 5, 2019.
As Data Science is becoming pervasive across so many industries, Hollywood is certainly not being left behind. Learn about how Big Data, analytics, and AI are now core drivers of the movies we watch and how we watch them.
Data Science, Industry, Marketing, Movies, Predictive Analytics, Recommender Systems
- Building a Recommender System, Part 2 - Jul 3, 2019.
This post explores an technique for collaborative filtering which uses latent factor models, a which naturally generalizes to deep learning approaches. Our approach will be implemented using Tensorflow and Keras.
Movies, Python, Recommendation Engine, Recommender Systems
- Building Recommender systems with Azure Machine Learning service - May 15, 2019.
Microsoft has provided a GitHub repository with Python best practice examples to facilitate the building and evaluation of recommendation systems using Azure Machine Learning services.
Azure ML, Machine Learning, Microsoft Azure, Recommender Systems
- Building a Recommender System - Apr 4, 2019.
A beginners guide to building a recommendation system, with a step-by-step guide on how to create a content-based filtering system to recommend movies for a user to watch.
Movies, Python, Recommendation Engine, Recommender Systems
- Word Embeddings in NLP and its Applications - Feb 20, 2019.
Word embeddings such as Word2Vec is a key AI method that bridges the human understanding of language to that of a machine and is essential to solving many NLP problems. Here we discuss applications of Word2Vec to Survey responses, comment analysis, recommendation engines, and more.
Applications, NLP, Recommender Systems, Word Embeddings, word2vec
- State of the art in AI and Machine Learning – highlights of papers with code - Feb 20, 2019.
We introduce papers with code, the free and open resource of state-of-the-art Machine Learning papers, code and evaluation tables.
AI, Machine Learning, Multitask Learning, NLP, Papers with code, Recommender Systems, Semantic Segmentation, TensorFlow, Transfer Learning
How LinkedIn Makes Personalized Recommendations via Photon-ML Machine Learning tool - Oct 16, 2017.
In this article we focus on the personalization aspect of model building and explain the modeling principle as well as how to implement Photon-ML so that it can scale to hundreds of millions of users.
Deepak Agarwal, LinkedIn, Machine Learning, Recommendation, Recommender Systems
- Recommendation System Algorithms: An Overview - Aug 22, 2017.
This post presents an overview of the main existing recommendation system algorithms, in order for data scientists to choose the best one according a business’s limitations and requirements.
Algorithms, Recommendations, Recommender Systems, Statsbot
- Recommender Systems: New Comprehensive Textbook by Charu Aggarwal - Apr 15, 2016.
Covers recommender systems comprehensively, both fundamentals and advanced topics, organized into: Algorithms and evaluation, recommendations in specific domains and contexts, and advanced topics and applications.
Book, Charu Aggarwal, Recommender Systems
- Netflix Prize Analyzed: Movie Ratings and Recommender Systems - Mar 18, 2016.
A 195-page monograph by a top-1% Netflix Prize contestant. Learn about the famous machine learning competition. Improve your machine learning skills. Learn how to build recommender systems.
Free ebook, Netflix, Recommender Systems
- 21 Must-Know Data Science Interview Questions and Answers, part 2 - Feb 20, 2016.
Second part of the answers to 20 Questions to Detect Fake Data Scientists, including controlling overfitting, experimental design, tall and wide data, understanding the validity of statistics in the media, and more.
Pages: 1 2 3
Anomaly Detection, Data Science, Data Visualization, Overfitting, Recommender Systems
- 9 Must-Have Datasets for Investigating Recommender Systems - Feb 11, 2016.
Gain some insight into a variety of useful datasets for recommender systems, including data descriptions, appropriate uses, and some practical comparison.
Datasets, Lab41, Recommender Systems
- 5 Tribes of Machine Learning – Questions and Answers - Nov 27, 2015.
Leading researcher Pedro Domingos answers questions on 5 tribes of Machine Learning, Master Algorithm, No Free Lunch Theorem, Unsupervised Learning, Ensemble methods, 360-degree recommender, and more.
Ensemble Methods, Machine Learning, Pedro Domingos, Recommender Systems
- How Big Data is used in Recommendation Systems to change our lives - Oct 30, 2015.
A Recommendation systems have impacted or even redefined our lives in many ways. It works in well-defined, logical phases which are data collection, ratings, and filtering.
Pages: 1 2 3
Amazon, Big Data, Kaushik Pal, Recommendations, Recommender Systems
