FileMood

Download [FreeCourseSite.com] Udemy - Building Recommender Systems with Machine Learning and AI

FreeCourseSite com Udemy Building Recommender Systems with Machine Learning and AI

Name

[FreeCourseSite.com] Udemy - Building Recommender Systems with Machine Learning and AI

 DOWNLOAD Copy Link

Total Size

4.8 GB

Total Files

223

Last Seen

2024-10-15 23:32

Hash

B80E4012E2F75F1D9CCEBB0727F380B94F979940

/01 Getting Started/

001 Udemy 101 Getting the Most From This Course-en.srt

4.0 KB

001 Udemy 101 Getting the Most From This Course.mp4

20.7 MB

002 [Activity] Install Anaconda course materials and create movie recommendations-en.srt

15.6 KB

002 [Activity] Install Anaconda course materials and create movie recommendations.mp4

109.1 MB

003 Course Roadmap-en.srt

8.5 KB

003 Course Roadmap.mp4

28.9 MB

004 Types of Recommenders-en.srt

6.8 KB

004 Types of Recommenders.mp4

28.1 MB

005 Understanding You through Implicit and Explicit Ratings-en.srt

9.0 KB

005 Understanding You through Implicit and Explicit Ratings.mp4

21.7 MB

006 Top-N Recommender Architecture-en.srt

11.9 KB

006 Top-N Recommender Architecture.mp4

38.9 MB

007 [Quiz] Review the basics of recommender systems.-en.srt

9.1 KB

007 [Quiz] Review the basics of recommender systems..mp4

22.3 MB

/02 Introduction to Python [Optional]/

008 [Activity] The Basics of Python-en.srt

8.9 KB

008 [Activity] The Basics of Python.mp4

45.1 MB

009 Data Structures in Python-en.srt

9.7 KB

009 Data Structures in Python.mp4

25.6 MB

010 Functions in Python-en.srt

5.3 KB

010 Functions in Python.mp4

12.9 MB

011 [Exercise] Booleans loops and a hands-on challenge-en.srt

6.4 KB

011 [Exercise] Booleans loops and a hands-on challenge.mp4

14.5 MB

/03 Evaluating Recommender Systems/

012 TrainTest and Cross Validation-en.srt

8.5 KB

012 TrainTest and Cross Validation.mp4

30.5 MB

013 Accuracy Metrics (RMSE MAE)-en.srt

8.7 KB

013 Accuracy Metrics (RMSE MAE).mp4

42.2 MB

014 Top-N Hit Rate - Many Ways-en.srt

9.4 KB

014 Top-N Hit Rate - Many Ways.mp4

25.7 MB

015 Coverage Diversity and Novelty-en.srt

10.8 KB

015 Coverage Diversity and Novelty.mp4

14.4 MB

016 Churn Responsiveness and AB Tests-en.srt

11.2 KB

016 Churn Responsiveness and AB Tests.mp4

63.9 MB

017 [Quiz] Review ways to measure your recommender.-en.srt

5.6 KB

017 [Quiz] Review ways to measure your recommender..mp4

13.5 MB

018 [Activity] Walkthrough of RecommenderMetrics.py-en.srt

13.1 KB

018 [Activity] Walkthrough of RecommenderMetrics.py.mp4

67.4 MB

019 [Activity] Walkthrough of TestMetrics.py-en.srt

10.9 KB

019 [Activity] Walkthrough of TestMetrics.py.mp4

57.0 MB

020 [Activity] Measure the Performance of SVD Recommendations-en.srt

5.1 KB

020 [Activity] Measure the Performance of SVD Recommendations.mp4

22.6 MB

/04 A Recommender Engine Framework/

021 Our Recommender Engine Architecture-en.srt

15.2 KB

021 Our Recommender Engine Architecture.mp4

34.3 MB

022 [Activity] Recommender Engine Walkthrough Part 1-en.srt

7.6 KB

022 [Activity] Recommender Engine Walkthrough Part 1.mp4

39.7 MB

023 [Activity] Recommender Engine Walkthrough Part 2-en.srt

8.1 KB

023 [Activity] Recommender Engine Walkthrough Part 2.mp4

41.5 MB

024 [Activity] Review the Results of our Algorithm Evaluation.-en.srt

6.5 KB

024 [Activity] Review the Results of our Algorithm Evaluation..mp4

36.2 MB

/05 Content-Based Filtering/

025 Content-Based Recommendations and the Cosine Similarity Metric-en.srt

18.3 KB

025 Content-Based Recommendations and the Cosine Similarity Metric.mp4

64.6 MB

026 K-Nearest-Neighbors and Content Recs-en.srt

8.3 KB

026 K-Nearest-Neighbors and Content Recs.mp4

20.6 MB

027 [Activity] Producing and Evaluating Content-Based Movie Recommendations-en.srt

10.6 KB

027 [Activity] Producing and Evaluating Content-Based Movie Recommendations.mp4

54.9 MB

028 [Activity] Bleeding Edge Alert Mise en Scene Recommendations-en.srt

8.8 KB

028 [Activity] Bleeding Edge Alert Mise en Scene Recommendations.mp4

48.8 MB

029 [Exercise] Dive Deeper into Content-Based Recommendations-en.srt

8.7 KB

029 [Exercise] Dive Deeper into Content-Based Recommendations.mp4

25.3 MB

/06 Neighborhood-Based Collaborative Filtering/

030 Measuring Similarity and Sparsity-en.srt

11.0 KB

030 Measuring Similarity and Sparsity.mp4

62.0 MB

031 Similarity Metrics-en.srt

19.3 KB

031 Similarity Metrics.mp4

32.2 MB

032 User-based Collaborative Filtering-en.srt

14.6 KB

032 User-based Collaborative Filtering.mp4

35.9 MB

033 [Activity] User-based Collaborative Filtering Hands-On-en.srt

9.8 KB

033 [Activity] User-based Collaborative Filtering Hands-On.mp4

51.0 MB

034 Item-based Collaborative Filtering-en.srt

9.0 KB

034 Item-based Collaborative Filtering.mp4

54.8 MB

035 [Activity] Item-based Collaborative Filtering Hands-On-en.srt

5.0 KB

035 [Activity] Item-based Collaborative Filtering Hands-On.mp4

28.1 MB

036 [Exercise] Tuning Collaborative Filtering Algorithms-en.srt

7.1 KB

036 [Exercise] Tuning Collaborative Filtering Algorithms.mp4

20.7 MB

037 [Activity] Evaluating Collaborative Filtering Systems Offline-en.srt

2.6 KB

037 [Activity] Evaluating Collaborative Filtering Systems Offline.mp4

16.2 MB

038 [Exercise] Measure the Hit Rate of Item-Based Collaborative Filtering-en.srt

4.6 KB

038 [Exercise] Measure the Hit Rate of Item-Based Collaborative Filtering.mp4

10.0 MB

039 KNN Recommenders-en.srt

8.4 KB

039 KNN Recommenders.mp4

26.1 MB

040 [Activity] Running User and Item-Based KNN on MovieLens-en.srt

4.8 KB

040 [Activity] Running User and Item-Based KNN on MovieLens.mp4

24.9 MB

041 [Exercise] Experiment with different KNN parameters.-en.srt

9.0 KB

041 [Exercise] Experiment with different KNN parameters..mp4

43.3 MB

042 Bleeding Edge Alert Translation-Based Recommendations-en.srt

5.0 KB

042 Bleeding Edge Alert Translation-Based Recommendations.mp4

22.5 MB

/07 Matrix Factorization Methods/

043 Principal Component Analysis (PCA)-en.srt

14.4 KB

043 Principal Component Analysis (PCA).mp4

64.2 MB

044 Singular Value Decomposition-en.srt

13.9 KB

044 Singular Value Decomposition.mp4

26.3 MB

045 [Activity] Running SVD and SVD on MovieLens-en.srt

6.5 KB

045 [Activity] Running SVD and SVD on MovieLens.mp4

39.3 MB

046 Improving on SVD-en.srt

9.3 KB

046 Improving on SVD.mp4

24.2 MB

047 [Exercise] Tune the hyperparameters on SVD-en.srt

4.1 KB

047 [Exercise] Tune the hyperparameters on SVD.mp4

13.1 MB

048 Bleeding Edge Alert Sparse Linear Methods (SLIM)-en.srt

7.7 KB

048 Bleeding Edge Alert Sparse Linear Methods (SLIM).mp4

27.7 MB

/08 Introduction to Deep Learning [Optional]/

049 Deep Learning Introduction-en.srt

3.4 KB

049 Deep Learning Introduction.mp4

18.5 MB

050 Deep Learning Pre-Requisites-en.srt

18.3 KB

050 Deep Learning Pre-Requisites.mp4

38.8 MB

051 History of Artificial Neural Networks-en.srt

23.0 KB

051 History of Artificial Neural Networks.mp4

88.3 MB

052 [Activity] Playing with Tensorflow-en.srt

23.8 KB

052 [Activity] Playing with Tensorflow.mp4

152.5 MB

053 Training Neural Networks-en.srt

12.8 KB

053 Training Neural Networks.mp4

40.2 MB

054 Tuning Neural Networks-en.srt

8.5 KB

054 Tuning Neural Networks.mp4

32.8 MB

055 Introduction to Tensorflow-en.srt

26.6 KB

055 Introduction to Tensorflow.mp4

97.0 MB

056 [Activity] Handwriting Recognition with Tensorflow part 1-en.srt

34.1 KB

056 [Activity] Handwriting Recognition with Tensorflow part 1.mp4

190.7 MB

057 [Activity] Handwriting Recognition with Tensorflow part 2-en.srt

13.7 KB

057 [Activity] Handwriting Recognition with Tensorflow part 2.mp4

60.4 MB

058 Introduction to Keras-en.srt

6.3 KB

058 Introduction to Keras.mp4

17.3 MB

059 [Activity] Handwriting Recognition with Keras-en.srt

20.1 KB

059 [Activity] Handwriting Recognition with Keras.mp4

93.0 MB

060 Classifier Patterns with Keras-en.srt

8.2 KB

060 Classifier Patterns with Keras.mp4

26.0 MB

061 [Exercise] Predict Political Parties of Politicians with Keras-en.srt

18.3 KB

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

105.1 MB

062 Intro to Convolutional Neural Networks (CNNs)-en.srt

18.4 KB

062 Intro to Convolutional Neural Networks (CNNs).mp4

82.0 MB

063 CNN Architectures-en.srt

6.4 KB

063 CNN Architectures.mp4

23.6 MB

064 [Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs)-en.srt

17.2 KB

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

86.3 MB

065 Intro to Recurrent Neural Networks (RNNs)-en.srt

15.9 KB

065 Intro to Recurrent Neural Networks (RNNs).mp4

52.1 MB

066 Training Recurrent Neural Networks-en.srt

6.8 KB

066 Training Recurrent Neural Networks.mp4

21.7 MB

067 [Activity] Sentiment Analysis of Movie Reviews using RNNs and Keras-en.srt

23.2 KB

067 [Activity] Sentiment Analysis of Movie Reviews using RNNs and Keras.mp4

125.6 MB

/09 Deep Learning for Recommender Systems/

068 Intro to Deep Learning for Recommenders-en.srt

4.9 KB

068 Intro to Deep Learning for Recommenders.mp4

44.7 MB

069 Restricted Boltzmann Machines (RBMs)-en.srt

16.6 KB

069 Restricted Boltzmann Machines (RBMs).mp4

33.2 MB

070 [Activity] Recommendations with RBMs part 1-en.srt

25.7 KB

070 [Activity] Recommendations with RBMs part 1.mp4

151.5 MB

071 [Activity] Recommendations with RBMs part 2-en.srt

14.4 KB

071 [Activity] Recommendations with RBMs part 2.mp4

80.5 MB

072 [Activity] Evaluating the RBM Recommender-en.srt

6.8 KB

072 [Activity] Evaluating the RBM Recommender.mp4

39.5 MB

073 [Exercise] Tuning Restricted Boltzmann Machines-en.srt

3.9 KB

073 [Exercise] Tuning Restricted Boltzmann Machines.mp4

35.2 MB

074 Exercise Results Tuning a RBM Recommender-en.srt

2.5 KB

074 Exercise Results Tuning a RBM Recommender.mp4

12.4 MB

075 Auto-Encoders for Recommendations Deep Learning for Recs-en.srt

9.6 KB

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

28.2 MB

076 [Activity] Recommendations with Deep Neural Networks-en.srt

13.7 KB

076 [Activity] Recommendations with Deep Neural Networks.mp4

79.1 MB

077 Clickstream Recommendations with RNNs-en.srt

15.5 KB

077 Clickstream Recommendations with RNNs.mp4

51.1 MB

078 [Exercise] Get GRU4Rec Working on your Desktop-en.srt

5.4 KB

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

7.8 MB

079 Exercise Results GRU4Rec in Action-en.srt

16.7 KB

079 Exercise Results GRU4Rec in Action.mp4

65.7 MB

080 Bleeding Edge Alert Deep Factorization Machines-en.srt

11.7 KB

080 Bleeding Edge Alert Deep Factorization Machines.mp4

60.1 MB

081 More Emerging Tech to Watch-en.srt

10.8 KB

081 More Emerging Tech to Watch.mp4

29.0 MB

/10 Scaling it Up/

082 [Activity] Introduction and Installation of Apache Spark-en.srt

8.4 KB

082 [Activity] Introduction and Installation of Apache Spark.mp4

55.9 MB

083 Apache Spark Architecture-en.srt

10.5 KB

083 Apache Spark Architecture.mp4

18.2 MB

084 [Activity] Movie Recommendations with Spark Matrix Factorization and ALS-en.srt

11.4 KB

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

58.3 MB

085 [Activity] Recommendations from 20 million ratings with Spark-en.srt

8.6 KB

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

53.1 MB

086 Amazon DSSTNE-en.srt

9.4 KB

086 Amazon DSSTNE.mp4

44.4 MB

087 DSSTNE in Action-en.srt

11.9 KB

087 DSSTNE in Action.mp4

122.3 MB

088 Scaling Up DSSTNE-en.srt

4.3 KB

088 Scaling Up DSSTNE.mp4

10.9 MB

089 AWS SageMaker and Factorization Machines-en.srt

8.6 KB

089 AWS SageMaker and Factorization Machines.mp4

16.3 MB

090 SageMaker in Action Factorization Machines on one million ratings in the cloud-en.srt

13.2 KB

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

71.7 MB

/11 Real-World Challenges of Recommender Systems/

091 The Cold Start Problem (and solutions)-en.srt

13.6 KB

091 The Cold Start Problem (and solutions).mp4

29.1 MB

092 [Exercise] Implement Random Exploration-en.srt

1.8 KB

092 [Exercise] Implement Random Exploration.mp4

2.3 MB

093 Exercise Solution Random Exploration-en.srt

4.3 KB

093 Exercise Solution Random Exploration.mp4

25.3 MB

094 Stoplists-en.srt

10.5 KB

094 Stoplists.mp4

20.9 MB

095 [Exercise] Implement a Stoplist-en.srt

1.2 KB

095 [Exercise] Implement a Stoplist.mp4

1.4 MB

096 Exercise Solution Implement a Stoplist-en.srt

4.4 KB

096 Exercise Solution Implement a Stoplist.mp4

28.0 MB

097 Filter Bubbles Trust and Outliers-en.srt

12.4 KB

097 Filter Bubbles Trust and Outliers.mp4

96.9 MB

098 [Exercise] Identify and Eliminate Outlier Users-en.srt

1.7 KB

098 [Exercise] Identify and Eliminate Outlier Users.mp4

1.9 MB

099 Exercise Solution Outlier Removal-en.srt

7.7 KB

099 Exercise Solution Outlier Removal.mp4

40.4 MB

100 Fraud The Perils of Clickstream and International Concerns-en.srt

9.9 KB

100 Fraud The Perils of Clickstream and International Concerns.mp4

61.1 MB

101 Temporal Effects and Value-Aware Recommendations-en.srt

7.7 KB

101 Temporal Effects and Value-Aware Recommendations.mp4

56.6 MB

/12 Case Studies/

102 Case Study YouTube Part 1-en.srt

7.4 KB

102 Case Study YouTube Part 1.mp4

28.2 MB

103 Case Study YouTube Part 2-en.srt

14.6 KB

103 Case Study YouTube Part 2.mp4

27.5 MB

104 Case Study Netflix Part 1-en.srt

7.8 KB

104 Case Study Netflix Part 1.mp4

28.9 MB

105 Case Study Netflix Part 2-en.srt

7.8 KB

105 Case Study Netflix Part 2.mp4

27.9 MB

/13 Hybrid Approaches/

106 Hybrid Recommenders and Exercise-en.srt

5.6 KB

106 Hybrid Recommenders and Exercise.mp4

19.3 MB

107 Exercise Solution Hybrid Recommenders-en.srt

8.5 KB

107 Exercise Solution Hybrid Recommenders.mp4

34.8 MB

/14 Wrapping Up/

108 More to Explore-en.srt

5.1 KB

108 More to Explore.mp4

40.8 MB

109 Bonus Lecture Companion Book and More Courses from Sundog Education-en.srt

1.7 KB

109 Bonus Lecture Companion Book and More Courses from Sundog Education.mp4

22.1 MB

109 Building-Recommender-Systems-book-on-Amazon.txt

0.0 KB

109 Sundog-Education-website.txt

0.0 KB

/

[CourseClub.NET].url

0.1 KB

[FCS Forum].url

0.1 KB

[FreeCourseSite.com].url

0.1 KB

 

Total files 223


Copyright © 2024 FileMood.com