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[CourseClub.NET] Packtpub - Building Recommender Systems with Machine Learning and AI
magnet:?xt=urn:btih:333a3d99c556019529a3d9ca01fd159b5894792b&dn=[CourseClub.NET] Packtpub - Building Recommender Systems with Machine Learning and AI
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Hash值:
333a3d99c556019529a3d9ca01fd159b5894792b
点击数:
219
文件大小:
2.89 GB
文件数量:
107
创建日期:
2020-1-16 15:09
最后访问:
2024-5-3 21:33
访问标签:
CourseClub
NET
Packtpub
-
Building
Recommender
Systems
with
Machine
Learning
and
AI
文件列表详情
01.Getting Started/0101.Install Anaconda, course materials, and create movie recommendations!.mp4 88.13 MB
01.Getting Started/0102.Course Roadmap.mp4 69.27 MB
01.Getting Started/0103.Types of Recommenders.mp4 14.11 MB
01.Getting Started/0104.Understanding You through Implicit and Explicit Ratings.mp4 9.2 MB
01.Getting Started/0105.Top-N Recommender Architecture.mp4 15.32 MB
01.Getting Started/0106.Review the basics of recommender systems..mp4 11.16 MB
02.Introduction to Python/0201.The Basics of Python.mp4 42 MB
02.Introduction to Python/0202.Data Structures in Python.mp4 11.59 MB
02.Introduction to Python/0203.Functions in Python.mp4 5.85 MB
02.Introduction to Python/0204.Booleans, loops, and a hands-on challenge.mp4 7.33 MB
03.Evaluating Recommender Systems/0301.TrainTest and Cross Validation.mp4 23.17 MB
03.Evaluating Recommender Systems/0302.Accuracy Metrics (RMSE, MAE).mp4 46.73 MB
03.Evaluating Recommender Systems/0303.Top-N Hit Rate - Many Ways.mp4 12.16 MB
03.Evaluating Recommender Systems/0304.Coverage, Diversity, and Novelty.mp4 7.94 MB
03.Evaluating Recommender Systems/0305.Churn, Responsiveness, and AB Tests.mp4 82.68 MB
03.Evaluating Recommender Systems/0306.Review ways to measure your recommender..mp4 8.26 MB
03.Evaluating Recommender Systems/0307.Walkthrough of RecommenderMetrics.py.mp4 38.78 MB
03.Evaluating Recommender Systems/0308.Walkthrough of TestMetrics.py.mp4 25.34 MB
03.Evaluating Recommender Systems/0309.Measure the Performance of SVD Recommendations.mp4 12.05 MB
04.A Recommender Engine Framework/0401.Our Recommender Engine Architecture.mp4 18.17 MB
04.A Recommender Engine Framework/0402.Recommender Engine Walkthrough, Part 1.mp4 18.55 MB
04.A Recommender Engine Framework/0403.Recommender Engine Walkthrough, Part 2.mp4 18.57 MB
04.A Recommender Engine Framework/0404.Review the Results of our Algorithm Evaluation..mp4 14.3 MB
05.Content-Based Filtering/0501.Content-Based Recommendations, and the Cosine Similarity Metric.mp4 38.47 MB
05.Content-Based Filtering/0502.K-Nearest-Neighbors and Content Recs.mp4 11.84 MB
05.Content-Based Filtering/0503.Producing and Evaluating Content-Based Movie Recommendations.mp4 27.89 MB
05.Content-Based Filtering/0504.Bleeding Edge Alert! Mise en Scene Recommendations.mp4 33.71 MB
05.Content-Based Filtering/0505.Dive Deeper into Content-Based Recommendations.mp4 10.66 MB
06.Neighborhood-Based Collaborative Filtering/0601.Measuring Similarity, and Sparsity.mp4 69.75 MB
06.Neighborhood-Based Collaborative Filtering/0602.Similarity Metrics.mp4 15.45 MB
06.Neighborhood-Based Collaborative Filtering/0603.User-based Collaborative Filtering.mp4 19.99 MB
06.Neighborhood-Based Collaborative Filtering/0604.User-based Collaborative Filtering, Hands-On.mp4 24.56 MB
06.Neighborhood-Based Collaborative Filtering/0605.Item-based Collaborative Filtering.mp4 61.59 MB
06.Neighborhood-Based Collaborative Filtering/0606.Item-based Collaborative Filtering, Hands-On.mp4 18.12 MB
06.Neighborhood-Based Collaborative Filtering/0607.Tuning Collaborative Filtering Algorithms.mp4 10.06 MB
06.Neighborhood-Based Collaborative Filtering/0608.Evaluating Collaborative Filtering Systems Offline.mp4 10.57 MB
06.Neighborhood-Based Collaborative Filtering/0609.Measure the Hit Rate of Item-Based Collaborative Filtering.mp4 4.43 MB
06.Neighborhood-Based Collaborative Filtering/0610.KNN Recommenders.mp4 21.88 MB
06.Neighborhood-Based Collaborative Filtering/0611.Running User and Item-Based KNN on MovieLens.mp4 19.63 MB
06.Neighborhood-Based Collaborative Filtering/0612.Experiment with different KNN parameters..mp4 38.78 MB
06.Neighborhood-Based Collaborative Filtering/0613.Bleeding Edge Alert! Translation-Based Recommendations.mp4 19.64 MB
07.Matrix Factorization Methods/0701.Principal Component Analysis (PCA).mp4 64.98 MB
07.Matrix Factorization Methods/0702.Singular Value Decomposition.mp4 12.98 MB
07.Matrix Factorization Methods/0703.Running SVD and SVD++ on MovieLens.mp4 23.12 MB
07.Matrix Factorization Methods/0704.Improving on SVD.mp4 9.69 MB
07.Matrix Factorization Methods/0705.Tune the hyperparameters on SVD.mp4 8.02 MB
07.Matrix Factorization Methods/0706.Bleeding Edge Alert! Sparse Linear Methods (SLIM).mp4 21.08 MB
08.Introduction to Deep Learning/0801.Deep Learning Introduction.mp4 22.8 MB
08.Introduction to Deep Learning/0802.Deep Learning Pre-Requisites.mp4 20.12 MB
08.Introduction to Deep Learning/0803.History of Artificial Neural Networks.mp4 40.44 MB
08.Introduction to Deep Learning/0804.[Activity] Playing with Tensorflow.mp4 116.91 MB
08.Introduction to Deep Learning/0805.Training Neural Networks.mp4 18.84 MB
08.Introduction to Deep Learning/0806.Tuning Neural Networks.mp4 13.11 MB
08.Introduction to Deep Learning/0807.Introduction to Tensorflow.mp4 43 MB
08.Introduction to Deep Learning/0808.[Activity] Handwriting Recognition with Tensorflow, part 1.mp4 92.89 MB
08.Introduction to Deep Learning/0809.[Activity] Handwriting Recognition with Tensorflow, part 2.mp4 27.4 MB
08.Introduction to Deep Learning/0810.Introduction to Keras.mp4 6.67 MB
08.Introduction to Deep Learning/0811.[Activity] Handwriting Recognition with Keras.mp4 46.94 MB
08.Introduction to Deep Learning/0812.Classifier Patterns with Keras.mp4 13.12 MB
08.Introduction to Deep Learning/0813.[Exercise] Predict Political Parties of Politicians with Keras.mp4 53.7 MB
08.Introduction to Deep Learning/0814.Intro to Convolutional Neural Networks (CNN_s).mp4 36.4 MB
08.Introduction to Deep Learning/0815.CNN Architectures.mp4 9.65 MB
08.Introduction to Deep Learning/0816.[Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs).mp4 42.41 MB
08.Introduction to Deep Learning/0817.Intro to Recurrent Neural Networks (RNN_s).mp4 22.49 MB
08.Introduction to Deep Learning/0818.Training Recurrent Neural Networks.mp4 10.1 MB
08.Introduction to Deep Learning/0819.[Activity] Sentiment Analysis of Movie Reviews using RNN_s and Keras.mp4 73.37 MB
09.Deep Learning for Recommender Systems/0901.Intro to Deep Learning for Recommenders.mp4 55.99 MB
09.Deep Learning for Recommender Systems/0902.Restricted Boltzmann Machines (RBM_s).mp4 15.93 MB
09.Deep Learning for Recommender Systems/0903.[Activity] Recommendations with RBM_s, part 1.mp4 50.52 MB
09.Deep Learning for Recommender Systems/0904.[Activity] Recommendations with RBM_s, part 2.mp4 26.41 MB
09.Deep Learning for Recommender Systems/0905.[Activity] Evaluating the RBM Recommender.mp4 19.85 MB
09.Deep Learning for Recommender Systems/0906.[Exercise] Tuning Restricted Boltzmann Machines.mp4 53.71 MB
09.Deep Learning for Recommender Systems/0907.Exercise Results Tuning a RBM Recommender.mp4 6.63 MB
09.Deep Learning for Recommender Systems/0908.Auto-Encoders for Recommendations Deep Learning for Recs.mp4 11.82 MB
09.Deep Learning for Recommender Systems/0909.[Activity] Recommendations with Deep Neural Networks.mp4 37.22 MB
09.Deep Learning for Recommender Systems/0910.Clickstream Recommendations with RNN_s.mp4 24.84 MB
09.Deep Learning for Recommender Systems/0911.[Exercise] Get GRU4Rec Working on your Desktop.mp4 3.88 MB
09.Deep Learning for Recommender Systems/0912.Exercise Results GRU4Rec in Action.mp4 41.06 MB
09.Deep Learning for Recommender Systems/0913.Bleeding Edge Alert! Deep Factorization Machines.mp4 44.31 MB
09.Deep Learning for Recommender Systems/0914.More Emerging Tech to Watch.mp4 14.16 MB
10.Scaling it up/1001.[Activity] Introduction and Installation of Apache Spark.mp4 40.04 MB
10.Scaling it up/1002.Apache Spark Architecture.mp4 9.37 MB
10.Scaling it up/1003.[Activity] Movie Recommendations with Spark, Matrix Factorization, and ALS.mp4 23.76 MB
10.Scaling it up/1004.[Activity] Recommendations from 20 million ratings with Spark.mp4 26.92 MB
10.Scaling it up/1005.Amazon DSSTNE.mp4 41.35 MB
10.Scaling it up/1006.DSSTNE in Action.mp4 61.12 MB
10.Scaling it up/1007.Scaling Up DSSTNE.mp4 4.82 MB
10.Scaling it up/1008.AWS SageMaker and Factorization Machines.mp4 7.95 MB
10.Scaling it up/1009.SageMaker in Action Factorization Machines on one million ratings, in the cloud.mp4 44.2 MB
11.11 Real-World Challenges of Recommender Systems/1101.The Cold Start Problem (and solutions).mp4 11.8 MB
11.11 Real-World Challenges of Recommender Systems/1102.[Exercise] Implement Random Exploration.mp4 1.19 MB
11.11 Real-World Challenges of Recommender Systems/1103.Exercise Solution Random Exploration.mp4 15.43 MB
11.11 Real-World Challenges of Recommender Systems/1104.Stoplists.mp4 8.67 MB
11.11 Real-World Challenges of Recommender Systems/1105.[Exercise] Implement a Stoplist.mp4 761.82 KB
11.11 Real-World Challenges of Recommender Systems/1106.Exercise Solution Implement a Stoplist.mp4 15.07 MB
11.11 Real-World Challenges of Recommender Systems/1107.Filter Bubbles, Trust, and Outliers.mp4 21.76 MB
11.11 Real-World Challenges of Recommender Systems/1108.[Exercise] Identify and Eliminate Outlier Users.mp4 1020.31 KB
11.11 Real-World Challenges of Recommender Systems/1109.Exercise Solution Outlier Removal.mp4 16.61 MB
11.11 Real-World Challenges of Recommender Systems/1110.Fraud, the Perils of Clickstream, and International Concerns.mp4 72.79 MB
11.11 Real-World Challenges of Recommender Systems/1111.Temporal Effects, and Value-Aware Recommendations.mp4 81.63 MB
12.Case Studies/1201.Case Study YouTube, Part 1.mp4 12.79 MB
12.Case Studies/1202.Case Study YouTube, Part 2.mp4 12.47 MB
12.Case Studies/1203.Case Study Netflix, Part 1.mp4 13.85 MB
12.Case Studies/1204.Case Study Netflix, Part 2.mp4 9.84 MB
13.Hybrid Approaches/1301.Hybrid Recommenders and Exercise.mp4 8.82 MB
13.Hybrid Approaches/1302.Exercise Solution Hybrid Recommenders.mp4 20.42 MB
14.Wrapping Up/1401.More to Explore.mp4 61.91 MB
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