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Recommender Systems Complete Course Beginner to Advanced · LearnSpace
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Recommender Systems Complete Course Beginner to Advanced

Курс от Packt
Средний≈ 10.2 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Dive into the world of Recurrent Neural Networks (RNNs) with this in-depth course designed to equip you with essential knowledge and hands-on skills using TensorFlow. Start with an introduction to the core concepts of sequence data and time series forecasting, then progress to understanding and implementing autoregressive linear models. Discover how to apply simple RNNs to solve many-to-one and many-to-many problems, with practical coding sessions in TensorFlow 2. Move beyond basics with modern RNN units like GRU and LSTM, mastering their application in complex signal prediction and overcoming long-distance dependency issues. Learn the intricacies of RNN architecture and prepare to tackle more challenging tasks such as image classification and stock return predictions. The course emphasizes practical coding exercises, ensuring you can confidently implement these techniques in real-world scenarios. Finally, explore natural language processing (NLP) applications, including embeddings, text preprocessing, and text classification using LSTMs. This course is structured to provide a thorough understanding of RNNs, empowering you to apply these deep learning models effectively in various domains. This course is perfect for developers, data scientists, and tech enthusiasts who want to learn how to build and implement recommender systems. Basic knowledge of Python and machine learning concepts is recommended but not required.

Навыки, которые вы освоите

Deep LearningTensorflowPredictive ModelingData PreprocessingTime Series Analysis and ForecastingNatural Language ProcessingArtificial Neural NetworksEmbeddingsAutoencodersMachine LearningRecurrent Neural Networks (RNNs)AI Personalization

Программа курса

3 модулей · 100 учебных материалов

01Introduction7 материалов

Introduction

Introduction to the Course 'Recommender Systems Complete Course Beginner to Advanced'ЧтениеModule and Instructor IntroductionВидеоAI SciencesВидеоCourse OutlineВидео

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Packt - Course Instructors

Преподаватель курса

Recommender Systems Complete Course Beginner to Advanced
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Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 10.2 ч

3 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский, Венгерский

Часть программы вашего университета
Machine Learning Recommender SystemsВидео
Deep Learning Recommender SystemsВидео
Full Course ResourcesЧтение
02Recommender Systems with Machine Learning64 материалов

Recommender Systems with Machine Learning

Motivation for Recommender System: Recommender Systems OverviewВидеоMotivation for Recommender System: Introduction to Recommender SystemsВидеоMotivation for Recommender System: Recommender Systems Process and GoalsВидеоMotivation for Recommender System: Generations of Recommender SystemsВидеоMotivation for Recommender System: Nexus of AI and Recommender SystemsВидеоMotivation for Recommender System: Applications and Real-World ChallengesВидеоMotivation for Recommender System: QuizВидеоMotivation for Recommender System: Quiz SolutionВидеоBasics of Recommender System: OverviewВидеоBasics of Recommender System: Taxonomy of Recommender SystemsВидеоBasics of Recommender System: ICMВидеоBasics of Recommender System: User Rating MatrixВидеоBasics of Recommender System: Quality of Recommender SystemВидеоBasics of Recommender System: Online Evaluation TechniquesВидеоBasics of Recommender System: Offline Evaluation TechniquesВидеоBasics of Recommender System: Data PartitioningВидеоBasics of Recommender System: Important ParametersВидеоBasics of Recommender System: Error Metric ComputationВидеоBasics of Recommender System: Content-Based FilteringВидеоBasics of Recommender System: Collaborative Filtering and User-Based Collaborative FilteringВидеоBasics of Recommender System: Item Model and Memory-Based Collaborative FilteringВидеоBasics of Recommender System: QuizВидеоBasics of Recommender System: Quiz SolutionВидеоMachine Learning for Recommender Systems: OverviewВидеоMachine Learning for Recommender Systems: Benefits of Machine LearningВидеоMachine Learning for Recommender Systems: Guidelines for MLВидеоMachine Learning for Recommender Systems: Design Approaches for MLВидеоMachine Learning for Recommender Systems: Content-Based FilteringВидеоMachine Learning for Recommender Systems: Data Preparation for Content-Based FilteringВидеоMachine Learning for Recommender Systems: Data Manipulation for Content-Based FilteringВидеоMachine Learning for Recommender Systems: Exploring Genres in Content-Based FilteringВидеоMachine Learning for Recommender Systems: tf-idf MatrixВидеоMachine Learning for Recommender Systems: Recommendation EngineВидеоMachine Learning for Recommender Systems: Making RecommendationsВидеоMachine Learning for Recommender Systems: Item-Based Collaborative FilteringВидеоMachine Learning for Recommender Systems: Item-Based Filtering Data PreparationВидеоMachine Learning for Recommender Systems: Age Distribution for UsersВидеоMachine Learning for Recommender Systems: Collaborative Filtering using KNNВидеоMachine Learning for Recommender Systems: Geographic FilteringВидеоMachine Learning for Recommender Systems: KNN ImplementationВидеоMachine Learning for Recommender Systems: Making Recommendations with Collaborative FilteringВидеоMachine Learning for Recommender Systems: User-Based Collaborative FilteringВидеоMachine Learning for Recommender Systems: QuizВидеоMachine Learning for Recommender Systems: Quiz SolutionВидеоProject 1: Song Recommendation System Using Content-Based Filtering: Project IntroductionВидеоProject 1: Song Recommendation System Using Content-Based Filtering: Dataset UsageВидеоProject 1: Song Recommendation System Using Content-Based Filtering: Missing ValuesВидеоProject 1: Song Recommendation System Using Content-Based Filtering: Exploring GenresВидеоProject 1: Song Recommendation System Using Content-Based Filtering: Occurrence CountВидеоProject 1: Song Recommendation System Using Content-Based Filtering: tf-idf ImplementationВидеоProject 1: Song Recommendation System Using Content-Based Filtering: Similarity IndexВидеоProject 1: Song Recommendation System Using Content-Based Filtering: Fuzzywuzzy ImplementationВидеоProject 1: Song Recommendation System Using Content-Based Filtering: Find Closest TitleВидеоProject 1: Song Recommendation System Using Content-Based Filtering: Making RecommendationsВидеоProject 2: Movie Recommendation System Using Collaborative Filtering: Project IntroductionВидеоProject 2: Movie Recommendation System Using Collaborative Filtering: Dataset DiscussionВидеоProject 2: Movie Recommendation System Using Collaborative Filtering: Rating PlotВидеоProject 2: Movie Recommendation System Using Collaborative Filtering: CountВидеоProject 2: Movie Recommendation System Using Collaborative Filtering: Logarithm of CountВидеоProject 2: Movie Recommendation System Using Collaborative Filtering: Active Users and Popular MoviesВидеоProject 2: Movie Recommendation System Using Collaborative Filtering: Create Collaborative FilterВидеоProject 2: Movie Recommendation System Using Collaborative Filtering: KNN ImplementationВидеоProject 2: Movie Recommendation System Using Collaborative Filtering: Making RecommendationsВидеоUnderstanding Recommender SystemsDIALOGUE
03Deep Learning for Recommender Systems: An Applied Approach29 материалов

Deep Learning for Recommender Systems: An Applied Approach

Deep Learning Foundation for Recommender Systems: Module IntroductionВидеоDeep Learning Foundation for Recommender Systems: OverviewВидеоDeep Learning Foundation for Recommender Systems: Deep Learning in Recommendation systemsВидеоDeep Learning Foundation for Recommender Systems: Inference After TrainingВидеоDeep Learning Foundation for Recommender Systems: Inference MechanismВидеоDeep Learning Foundation for Recommender Systems: Embeddings and User ContextВидеоDeep Learning Foundation for Recommender Systems: Neural Collaborative FilteringВидеоDeep Learning Foundation for Recommender Systems: VAE Collaborative FilteringВидеоDeep Learning Foundation for Recommender Systems: Strengths and Weaknesses of DL ModelsВидеоDeep Learning Foundation for Recommender Systems: Deep Learning QuizВидеоDeep Learning Foundation for Recommender Systems: Deep Learning Quiz SolutionВидеоProject Amazon Product Recommendation System: Module OverviewВидеоProject Amazon Product Recommendation System: TensorFlow RecommendersВидеоProject Amazon Product Recommendation System: Two-Tower ModelВидеоProject Amazon Product Recommendation System: Project OverviewВидеоProject Amazon Product Recommendation System: Download LibrariesВидеоProject Amazon Product Recommendation System: Data Visualization with WordCloudВидеоProject Amazon Product Recommendation System: Make Tensors from DataFrameВидеоProject Amazon Product Recommendation System: Rating Our DataВидеоProject Amazon Product Recommendation System: Random Train-Test SplitВидеоProject Amazon Product Recommendation System: Making the Model and Query TowerВидеоProject Amazon Product Recommendation System: Candidate Tower and Retrieval SystemВидеоProject Amazon Product Recommendation System: Compute LossВидеоProject Amazon Product Recommendation System: Train and ValidationВидеоProject Amazon Product Recommendation System: Accuracy Versus RecommendationsВидеоProject Amazon Product Recommendation System: Making RecommendationsВидеоConclusion to the Course 'Recommender Systems Complete Course Beginner to Advanced'ЧтениеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание