[CourseClub NET] Packtpub - Building Recommender Systems with Machine Learning and AI

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Name:[CourseClub NET] Packtpub - Building Recommender Systems with Machine Learning and AI

Total Size: 2.89 GB

Magnet: Magnet Link

Seeds: 23

Leechers: 29

Stream: Watch Full Movie @ Movie4u

Last Updated: 2018-09-28 19:07:05 (Update Now)

Torrent added: 2018-09-28 20:07:01

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Torrent Files List

01.Getting Started (Size: 2.89 GB) (Files: 110)

 01.Getting Started

  0101.Install Anaconda, course materials, and create movie recommendations!.mp4

88.13 MB

  0102.Course Roadmap.mp4

69.27 MB

  0103.Types of Recommenders.mp4

14.11 MB

  0104.Understanding You through Implicit and Explicit Ratings.mp4

9.20 MB

  0105.Top-N Recommender Architecture.mp4

15.32 MB

  0106.Review the basics of recommender systems..mp4

11.16 MB

 02.Introduction to Python

  0201.The Basics of Python.mp4

42.00 MB

  0202.Data Structures in Python.mp4

11.59 MB

  0203.Functions in Python.mp4

5.85 MB

  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

  0302.Accuracy Metrics (RMSE, MAE).mp4

46.73 MB

  0303.Top-N Hit Rate - Many Ways.mp4

12.16 MB

  0304.Coverage, Diversity, and Novelty.mp4

7.94 MB

  0305.Churn, Responsiveness, and AB Tests.mp4

82.68 MB

  0306.Review ways to measure your recommender..mp4

8.26 MB

  0307.Walkthrough of RecommenderMetrics.py.mp4

38.78 MB

  0308.Walkthrough of TestMetrics.py.mp4

25.34 MB

  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

  0402.Recommender Engine Walkthrough, Part 1.mp4

18.55 MB

  0403.Recommender Engine Walkthrough, Part 2.mp4

18.57 MB

  0404.Review the Results of our Algorithm Evaluation..mp4

14.30 MB

 05.Content-Based Filtering

  0501.Content-Based Recommendations, and the Cosine Similarity Metric.mp4

38.47 MB

  0502.K-Nearest-Neighbors and Content Recs.mp4

11.84 MB

  0503.Producing and Evaluating Content-Based Movie Recommendations.mp4

27.89 MB

  0504.Bleeding Edge Alert! Mise en Scene Recommendations.mp4

33.71 MB

  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

  0602.Similarity Metrics.mp4

15.45 MB

  0603.User-based Collaborative Filtering.mp4

19.99 MB

  0604.User-based Collaborative Filtering, Hands-On.mp4

24.56 MB

  0605.Item-based Collaborative Filtering.mp4

61.59 MB

  0606.Item-based Collaborative Filtering, Hands-On.mp4

18.12 MB

  0607.Tuning Collaborative Filtering Algorithms.mp4

10.06 MB

  0608.Evaluating Collaborative Filtering Systems Offline.mp4

10.57 MB

  0609.Measure the Hit Rate of Item-Based Collaborative Filtering.mp4

4.43 MB

  0610.KNN Recommenders.mp4

21.88 MB

  0611.Running User and Item-Based KNN on MovieLens.mp4

19.63 MB

  0612.Experiment with different KNN parameters..mp4

38.78 MB

  0613.Bleeding Edge Alert! Translation-Based Recommendations.mp4

19.64 MB

 07.Matrix Factorization Methods

  0701.Principal Component Analysis (PCA).mp4

64.98 MB

  0702.Singular Value Decomposition.mp4

12.98 MB

  0703.Running SVD and SVD++ on MovieLens.mp4

23.12 MB

  0704.Improving on SVD.mp4

9.69 MB

  0705.Tune the hyperparameters on SVD.mp4

8.02 MB

  0706.Bleeding Edge Alert! Sparse Linear Methods (SLIM).mp4

21.08 MB

 08.Introduction to Deep Learning

  0801.Deep Learning Introduction.mp4

22.80 MB

  0802.Deep Learning Pre-Requisites.mp4

20.12 MB

  0803.History of Artificial Neural Networks.mp4

40.44 MB

  0804.[Activity] Playing with Tensorflow.mp4

116.91 MB

  0805.Training Neural Networks.mp4

18.84 MB

  0806.Tuning Neural Networks.mp4

13.11 MB

  0807.Introduction to Tensorflow.mp4

43.00 MB

  0808.[Activity] Handwriting Recognition with Tensorflow, part 1.mp4

92.89 MB

  0809.[Activity] Handwriting Recognition with Tensorflow, part 2.mp4

27.40 MB

  0810.Introduction to Keras.mp4

6.67 MB

  0811.[Activity] Handwriting Recognition with Keras.mp4

46.94 MB

  0812.Classifier Patterns with Keras.mp4

13.12 MB

  0813.[Exercise] Predict Political Parties of Politicians with Keras.mp4

53.70 MB

  0814.Intro to Convolutional Neural Networks (CNN_s).mp4

36.40 MB

  0815.CNN Architectures.mp4

9.65 MB

  0816.[Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs).mp4

42.41 MB

  0817.Intro to Recurrent Neural Networks (RNN_s).mp4

22.49 MB

  0818.Training Recurrent Neural Networks.mp4

10.10 MB

  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

  0902.Restricted Boltzmann Machines (RBM_s).mp4

15.93 MB

  0903.[Activity] Recommendations with RBM_s, part 1.mp4

50.52 MB

  0904.[Activity] Recommendations with RBM_s, part 2.mp4

26.41 MB

  0905.[Activity] Evaluating the RBM Recommender.mp4

19.85 MB

  0906.[Exercise] Tuning Restricted Boltzmann Machines.mp4

53.71 MB

  0907.Exercise Results Tuning a RBM Recommender.mp4

6.63 MB

  0908.Auto-Encoders for Recommendations Deep Learning for Recs.mp4

11.82 MB

  0909.[Activity] Recommendations with Deep Neural Networks.mp4

37.22 MB

  0910.Clickstream Recommendations with RNN_s.mp4

24.84 MB

  0911.[Exercise] Get GRU4Rec Working on your Desktop.mp4

3.88 MB

  0912.Exercise Results GRU4Rec in Action.mp4

41.06 MB

  0913.Bleeding Edge Alert! Deep Factorization Machines.mp4

44.31 MB

  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

  1002.Apache Spark Architecture.mp4

9.37 MB

  1003.[Activity] Movie Recommendations with Spark, Matrix Factorization, and ALS.mp4

23.76 MB

  1004.[Activity] Recommendations from 20 million ratings with Spark.mp4

26.92 MB

  1005.Amazon DSSTNE.mp4

41.35 MB

  1006.DSSTNE in Action.mp4

61.12 MB

  1007.Scaling Up DSSTNE.mp4

4.82 MB

  1008.AWS SageMaker and Factorization Machines.mp4

7.95 MB

  1009.SageMaker in Action Factorization Machines on one million ratings, in the cloud.mp4

44.20 MB

 11.11 Real-World Challenges of Recommender Systems

  1101.The Cold Start Problem (and solutions).mp4

11.80 MB

  1102.[Exercise] Implement Random Exploration.mp4

1.19 MB

  1103.Exercise Solution Random Exploration.mp4

15.43 MB


8.67 MB

  1105.[Exercise] Implement a Stoplist.mp4

761.82 KB

  1106.Exercise Solution Implement a Stoplist.mp4

15.07 MB

  1107.Filter Bubbles, Trust, and Outliers.mp4

21.76 MB

  1108.[Exercise] Identify and Eliminate Outlier Users.mp4

1.00 MB

  1109.Exercise Solution Outlier Removal.mp4

16.61 MB

  1110.Fraud, the Perils of Clickstream, and International Concerns.mp4

72.79 MB

  1111.Temporal Effects, and Value-Aware Recommendations.mp4

81.63 MB

 12.Case Studies

  1201.Case Study YouTube, Part 1.mp4

12.79 MB

  1202.Case Study YouTube, Part 2.mp4

12.47 MB

  1203.Case Study Netflix, Part 1.mp4

13.85 MB

  1204.Case Study Netflix, Part 2.mp4

9.84 MB

 13.Hybrid Approaches

  1301.Hybrid Recommenders and Exercise.mp4

8.82 MB

  1302.Exercise Solution Hybrid Recommenders.mp4

20.42 MB

 14.Wrapping Up

  1401.More to Explore.mp4

61.91 MB

 Exercise Files


1.70 MB


0.12 KB


0.05 KB


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Torrent description

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