Kung-Hsiang, Huang (Steeve)inRosetta.ai Taiwan BlogA Deep Dive into Latent Dirichlet Allocation (LDA) and Its Applications on Recommender SystemLatent Dirichlet Allocation (LDA) is a topic modeling algorithm for discovering the underlying topics in corpora in an unsupervised…Feb 2, 20201Feb 2, 20201
Abhishek SharmainTowards Data ScienceNeural Collaborative FilteringSupercharging collaborative filtering with neural networksDec 16, 20196Dec 16, 20196
Benjamin WanginTowards Data ScienceRanking Evaluation Metrics for Recommender SystemsVarious evaluation metrics are used for evaluating the effectiveness of a recommender. We will focus mostly on ranking related metrics…Jan 18, 2021Jan 18, 2021
Zain ul AbideenOne-Stop Guide for Production Recommendation SystemsCandidate Generation, SSR for CG, ANN Search, Ranking, Evaluation Metrics, and Architectural paradigm of Real-time RecsysNov 21, 20232Nov 21, 20232
Francesco CasalegnoinTowards Data ScienceRecommender Systems — A Complete Guide to Machine Learning ModelsLeveraging data to help users discovering new contentsNov 25, 20222Nov 25, 20222
Eric LundquistinTowards Data ScienceFactorization Machines for Item Recommendation with Implicit Feedback DataGo beyond classic Matrix Factorization approaches to include user/item auxiliary features and directly optimize item rank-orderJun 28, 20206Jun 28, 20206
Mehul GuptainData Science in your pocketRecommendation Systems using Factorization Machines with examples and codesunderstanding the maths behind Factorization MachinesAug 7, 2023Aug 7, 2023
Angelina YangLarge-scale Recommendation System In ProductionRecommendation systems are critical to the success of today’s online commercial platforms.Aug 27, 2022Aug 27, 2022
Christian FreischlaginTowards Data ScienceCombining numerical and text features in deep neural networksIn applied machine learning, data often consists of multiple data types, e.g. text and numerical data. To build a model which combines…May 19, 20206May 19, 20206
SciforceinSciforceDeep Learning Based Recommender SystemsRecommender systems are lifesavers in the infinite seething sea of e-commerce, improving customer experience. Recommender engines are…Apr 30, 20211Apr 30, 20211
Sanket DoshiinTowards Data ScienceBrief on Recommender SystemsDifferent types of recommendation methods used in industries.Feb 10, 2019Feb 10, 2019
Denise CheninTowards Data ScienceRecommendation System — Matrix FactorizationWalk Through Recommender System of Matrix FactorizationJul 8, 20206Jul 8, 20206
David ChonginTowards Data ScienceWhy We Use Sparse Matrices for Recommender SystemsIntroduction to SciPy’s Sparse ModuleMay 9, 2020May 9, 2020
Jakub AdamczykinTowards Data Sciencek nearest neighbors computational complexityUnderstanding the computational cost of kNN algorithm, with case study examplesAug 7, 20203Aug 7, 20203
Mahmoud HarmouchinTowards Data Science17 types of similarity and dissimilarity measures used in data science.The following article explains various methods for computing distances and showing their instances in our daily lives. Additionally, it…Mar 13, 202117Mar 13, 202117
Haneul Kim[Paper review] Monolith: TikTok’s Real-time Recommender System.TikTok’s flexible architecture that allows both real-time and batch recommender system.Nov 19, 20222Nov 19, 20222
Meta HeuristicML System Design: TikTok recommender appTikTok is a highly successful consumer app that relies on proven machine learning algorithms for user engagement. How hypothetical system…Jul 20, 20221Jul 20, 20221
VatsalinTowards Data ScienceRecommendation Systems ExplainedExplaining & Implementing Content Based, Collaborative Filtering & Hybrid Recommendation Systems in PythonJul 12, 20217Jul 12, 20217
Nidhi UpretiUnderstanding System Design of Netflix: Backend Architecture and Cloud ServicesIntroduction:Aug 27, 202221Aug 27, 202221
Baptiste RoccainTowards Data ScienceIntroduction to recommender systemsOverview of some major recommendation algorithms.Jun 2, 201918Jun 2, 201918
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