| 0101.Install Anaconda, course materials, and create movie recommendations!.mp4 | 88.1 MB | ||
| 0102.Course Roadmap.mp4 | 69.3 MB | ||
| 0103.Types of Recommenders.mp4 | 14.1 MB | ||
| 0104.Understanding You through Implicit and Explicit Ratings.mp4 | 9.2 MB | ||
| 0105.Top-N Recommender Architecture.mp4 | 15.3 MB | ||
| 0106.Review the basics of recommender systems..mp4 | 11.2 MB | ||
| 0201.The Basics of Python.mp4 | 42 MB | ||
| 0202.Data Structures in Python.mp4 | 11.6 MB | ||
| 0203.Functions in Python.mp4 | 5.9 MB | ||
| 0204.Booleans, loops, and a hands-on challenge.mp4 | 7.3 MB | ||
| 0301.TrainTest and Cross Validation.mp4 | 23.2 MB | ||
| 0302.Accuracy Metrics (RMSE, MAE).mp4 | 46.7 MB | ||
| 0303.Top-N Hit Rate - Many Ways.mp4 | 12.2 MB | ||
| 0304.Coverage, Diversity, and Novelty.mp4 | 7.9 MB | ||
| 0305.Churn, Responsiveness, and AB Tests.mp4 | 82.7 MB | ||
| 0306.Review ways to measure your recommender..mp4 | 8.3 MB | ||
| 0307.Walkthrough of RecommenderMetrics.py.mp4 | 38.8 MB | ||
| 0308.Walkthrough of TestMetrics.py.mp4 | 25.3 MB | ||
| 0309.Measure the Performance of SVD Recommendations.mp4 | 12 MB | ||
| 0401.Our Recommender Engine Architecture.mp4 | 18.2 MB | ||
| 0402.Recommender Engine Walkthrough, Part 1.mp4 | 18.6 MB | ||
| 0403.Recommender Engine Walkthrough, Part 2.mp4 | 18.6 MB | ||
| 0404.Review the Results of our Algorithm Evaluation..mp4 | 14.3 MB | ||
| 0501.Content-Based Recommendations, and the Cosine Similarity Metric.mp4 | 38.5 MB | ||
| 0502.K-Nearest-Neighbors and Content Recs.mp4 | 11.8 MB | ||
| 0503.Producing and Evaluating Content-Based Movie Recommendations.mp4 | 27.9 MB | ||
| 0504.Bleeding Edge Alert! Mise en Scene Recommendations.mp4 | 33.7 MB | ||
| 0505.Dive Deeper into Content-Based Recommendations.mp4 | 10.7 MB | ||
| 0601.Measuring Similarity, and Sparsity.mp4 | 69.7 MB | ||
| 0602.Similarity Metrics.mp4 | 15.4 MB | ||
| 0603.User-based Collaborative Filtering.mp4 | 20 MB | ||
| 0604.User-based Collaborative Filtering, Hands-On.mp4 | 24.6 MB | ||
| 0605.Item-based Collaborative Filtering.mp4 | 61.6 MB | ||
| 0606.Item-based Collaborative Filtering, Hands-On.mp4 | 18.1 MB | ||
| 0607.Tuning Collaborative Filtering Algorithms.mp4 | 10.1 MB | ||
| 0608.Evaluating Collaborative Filtering Systems Offline.mp4 | 10.6 MB | ||
| 0609.Measure the Hit Rate of Item-Based Collaborative Filtering.mp4 | 4.4 MB | ||
| 0610.KNN Recommenders.mp4 | 21.9 MB | ||
| 0611.Running User and Item-Based KNN on MovieLens.mp4 | 19.6 MB | ||
| 0612.Experiment with different KNN parameters..mp4 | 38.8 MB | ||
| 0613.Bleeding Edge Alert! Translation-Based Recommendations.mp4 | 19.6 MB | ||
| 0701.Principal Component Analysis (PCA).mp4 | 65 MB | ||
| 0702.Singular Value Decomposition.mp4 | 13 MB | ||
| 0703.Running SVD and SVD++ on MovieLens.mp4 | 23.1 MB | ||
| 0704.Improving on SVD.mp4 | 9.7 MB | ||
| 0705.Tune the hyperparameters on SVD.mp4 | 8 MB | ||
| 0706.Bleeding Edge Alert! Sparse Linear Methods (SLIM).mp4 | 21.1 MB | ||
| 0801.Deep Learning Introduction.mp4 | 22.8 MB | ||
| 0802.Deep Learning Pre-Requisites.mp4 | 20.1 MB | ||
| 0803.History of Artificial Neural Networks.mp4 | 40.4 MB | ||
| 0804.[Activity] Playing with Tensorflow.mp4 | 116.9 MB | ||
| 0805.Training Neural Networks.mp4 | 18.8 MB | ||
| 0806.Tuning Neural Networks.mp4 | 13.1 MB | ||
| 0807.Introduction to Tensorflow.mp4 | 43 MB | ||
| 0808.[Activity] Handwriting Recognition with Tensorflow, part 1.mp4 | 92.9 MB | ||
| 0809.[Activity] Handwriting Recognition with Tensorflow, part 2.mp4 | 27.4 MB | ||
| 0810.Introduction to Keras.mp4 | 6.7 MB | ||
| 0811.[Activity] Handwriting Recognition with Keras.mp4 | 46.9 MB | ||
| 0812.Classifier Patterns with Keras.mp4 | 13.1 MB | ||
| 0813.[Exercise] Predict Political Parties of Politicians with Keras.mp4 | 53.7 MB | ||
| 0814.Intro to Convolutional Neural Networks (CNN_s).mp4 | 36.4 MB | ||
| 0815.CNN Architectures.mp4 | 9.6 MB | ||
| 0816.[Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs).mp4 | 42.4 MB | ||
| 0817.Intro to Recurrent Neural Networks (RNN_s).mp4 | 22.5 MB | ||
| 0818.Training Recurrent Neural Networks.mp4 | 10.1 MB | ||
| 0819.[Activity] Sentiment Analysis of Movie Reviews using RNN_s and Keras.mp4 | 73.4 MB | ||
| 0901.Intro to Deep Learning for Recommenders.mp4 | 56 MB | ||
| 0902.Restricted Boltzmann Machines (RBM_s).mp4 | 15.9 MB | ||
| 0903.[Activity] Recommendations with RBM_s, part 1.mp4 | 50.5 MB | ||
| 0904.[Activity] Recommendations with RBM_s, part 2.mp4 | 26.4 MB | ||
| 0905.[Activity] Evaluating the RBM Recommender.mp4 | 19.8 MB | ||
| 0906.[Exercise] Tuning Restricted Boltzmann Machines.mp4 | 53.7 MB | ||
| 0907.Exercise Results Tuning a RBM Recommender.mp4 | 6.6 MB | ||
| 0908.Auto-Encoders for Recommendations Deep Learning for Recs.mp4 | 11.8 MB | ||
| 0909.[Activity] Recommendations with Deep Neural Networks.mp4 | 37.2 MB | ||
| 0910.Clickstream Recommendations with RNN_s.mp4 | 24.8 MB | ||
| 0911.[Exercise] Get GRU4Rec Working on your Desktop.mp4 | 3.9 MB | ||
| 0912.Exercise Results GRU4Rec in Action.mp4 | 41.1 MB | ||
| 0913.Bleeding Edge Alert! Deep Factorization Machines.mp4 | 44.3 MB | ||
| 0914.More Emerging Tech to Watch.mp4 | 14.2 MB | ||
| 1001.[Activity] Introduction and Installation of Apache Spark.mp4 | 40 MB | ||
| 1002.Apache Spark Architecture.mp4 | 9.4 MB | ||
| 1003.[Activity] Movie Recommendations with Spark, Matrix Factorization, and ALS.mp4 | 23.8 MB | ||
| 1004.[Activity] Recommendations from 20 million ratings with Spark.mp4 | 26.9 MB | ||
| 1005.Amazon DSSTNE.mp4 | 41.4 MB | ||
| 1006.DSSTNE in Action.mp4 | 61.1 MB | ||
| 1007.Scaling Up DSSTNE.mp4 | 4.8 MB | ||
| 1008.AWS SageMaker and Factorization Machines.mp4 | 8 MB | ||
| 1009.SageMaker in Action Factorization Machines on one million ratings, in the cloud.mp4 | 44.2 MB | ||
| 1101.The Cold Start Problem (and solutions).mp4 | 11.8 MB | ||
| 1102.[Exercise] Implement Random Exploration.mp4 | 1.2 MB | ||
| 1103.Exercise Solution Random Exploration.mp4 | 15.4 MB | ||
| 1104.Stoplists.mp4 | 8.7 MB | ||
| 1105.[Exercise] Implement a Stoplist.mp4 | 761.8 KB | ||
| 1106.Exercise Solution Implement a Stoplist.mp4 | 15.1 MB | ||
| 1107.Filter Bubbles, Trust, and Outliers.mp4 | 21.8 MB | ||
| 1109.Exercise Solution Outlier Removal.mp4 | 16.6 MB | ||
| 1110.Fraud, the Perils of Clickstream, and International Concerns.mp4 | 72.8 MB | ||
| 1111.Temporal Effects, and Value-Aware Recommendations.mp4 | 81.6 MB | ||
| 1201.Case Study YouTube, Part 1.mp4 | 12.8 MB | ||
| 1202.Case Study YouTube, Part 2.mp4 | 12.5 MB | ||
| 1203.Case Study Netflix, Part 1.mp4 | 13.9 MB | ||
| 1204.Case Study Netflix, Part 2.mp4 | 9.8 MB | ||
| 1301.Hybrid Recommenders and Exercise.mp4 | 8.8 MB | ||
| 1302.Exercise Solution Hybrid Recommenders.mp4 | 20.4 MB | ||
| 1401.More to Explore.mp4 | 61.9 MB | ||
| [CourseClub.NET].url | 102.4 B | ||
| [DesireCourse.Com].url | 0 B | ||
| exercise_files.zip | 1.7 MB | ||
| ▲ 109 total files | |||
[Packtpub] Building Recommender Systems with Machine Learning and AI
Help people discover new products and content with deep learning, neural networks, and machine learning recommendations.
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