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[FreeCourseSite.com] Udemy - Building Recommender Systems with Machine Learning and AI
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b80e4012e2f75f1d9ccebb0727f380b94f979940
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最近下载:
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文档列表
08 Introduction to Deep Learning [Optional]/056 [Activity] Handwriting Recognition with Tensorflow part 1.mp4
190.7 MB
08 Introduction to Deep Learning [Optional]/052 [Activity] Playing with Tensorflow.mp4
152.5 MB
09 Deep Learning for Recommender Systems/070 [Activity] Recommendations with RBMs part 1.mp4
151.5 MB
08 Introduction to Deep Learning [Optional]/067 [Activity] Sentiment Analysis of Movie Reviews using RNNs and Keras.mp4
125.6 MB
10 Scaling it Up/087 DSSTNE in Action.mp4
122.3 MB
01 Getting Started/002 [Activity] Install Anaconda course materials and create movie recommendations.mp4
109.1 MB
08 Introduction to Deep Learning [Optional]/061 [Exercise] Predict Political Parties of Politicians with Keras.mp4
105.1 MB
08 Introduction to Deep Learning [Optional]/055 Introduction to Tensorflow.mp4
97.0 MB
11 Real-World Challenges of Recommender Systems/097 Filter Bubbles Trust and Outliers.mp4
96.9 MB
08 Introduction to Deep Learning [Optional]/059 [Activity] Handwriting Recognition with Keras.mp4
93.0 MB
08 Introduction to Deep Learning [Optional]/051 History of Artificial Neural Networks.mp4
88.3 MB
08 Introduction to Deep Learning [Optional]/064 [Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs).mp4
86.3 MB
08 Introduction to Deep Learning [Optional]/062 Intro to Convolutional Neural Networks (CNNs).mp4
82.0 MB
09 Deep Learning for Recommender Systems/071 [Activity] Recommendations with RBMs part 2.mp4
80.5 MB
09 Deep Learning for Recommender Systems/076 [Activity] Recommendations with Deep Neural Networks.mp4
79.1 MB
10 Scaling it Up/090 SageMaker in Action Factorization Machines on one million ratings in the cloud.mp4
71.7 MB
03 Evaluating Recommender Systems/018 [Activity] Walkthrough of RecommenderMetrics.py.mp4
67.4 MB
09 Deep Learning for Recommender Systems/079 Exercise Results GRU4Rec in Action.mp4
65.7 MB
05 Content-Based Filtering/025 Content-Based Recommendations and the Cosine Similarity Metric.mp4
64.6 MB
07 Matrix Factorization Methods/043 Principal Component Analysis (PCA).mp4
64.2 MB
03 Evaluating Recommender Systems/016 Churn Responsiveness and AB Tests.mp4
63.9 MB
06 Neighborhood-Based Collaborative Filtering/030 Measuring Similarity and Sparsity.mp4
62.0 MB
11 Real-World Challenges of Recommender Systems/100 Fraud The Perils of Clickstream and International Concerns.mp4
61.1 MB
08 Introduction to Deep Learning [Optional]/057 [Activity] Handwriting Recognition with Tensorflow part 2.mp4
60.4 MB
09 Deep Learning for Recommender Systems/080 Bleeding Edge Alert Deep Factorization Machines.mp4
60.1 MB
10 Scaling it Up/084 [Activity] Movie Recommendations with Spark Matrix Factorization and ALS.mp4
58.3 MB
03 Evaluating Recommender Systems/019 [Activity] Walkthrough of TestMetrics.py.mp4
57.0 MB
11 Real-World Challenges of Recommender Systems/101 Temporal Effects and Value-Aware Recommendations.mp4
56.6 MB
10 Scaling it Up/082 [Activity] Introduction and Installation of Apache Spark.mp4
55.9 MB
05 Content-Based Filtering/027 [Activity] Producing and Evaluating Content-Based Movie Recommendations.mp4
54.9 MB
06 Neighborhood-Based Collaborative Filtering/034 Item-based Collaborative Filtering.mp4
54.8 MB
10 Scaling it Up/085 [Activity] Recommendations from 20 million ratings with Spark.mp4
53.1 MB
08 Introduction to Deep Learning [Optional]/065 Intro to Recurrent Neural Networks (RNNs).mp4
52.1 MB
09 Deep Learning for Recommender Systems/077 Clickstream Recommendations with RNNs.mp4
51.1 MB
06 Neighborhood-Based Collaborative Filtering/033 [Activity] User-based Collaborative Filtering Hands-On.mp4
51.0 MB
05 Content-Based Filtering/028 [Activity] Bleeding Edge Alert Mise en Scene Recommendations.mp4
48.8 MB
02 Introduction to Python [Optional]/008 [Activity] The Basics of Python.mp4
45.1 MB
09 Deep Learning for Recommender Systems/068 Intro to Deep Learning for Recommenders.mp4
44.7 MB
10 Scaling it Up/086 Amazon DSSTNE.mp4
44.4 MB
06 Neighborhood-Based Collaborative Filtering/041 [Exercise] Experiment with different KNN parameters..mp4
43.3 MB
03 Evaluating Recommender Systems/013 Accuracy Metrics (RMSE MAE).mp4
42.2 MB
04 A Recommender Engine Framework/023 [Activity] Recommender Engine Walkthrough Part 2.mp4
41.5 MB
14 Wrapping Up/108 More to Explore.mp4
40.8 MB
11 Real-World Challenges of Recommender Systems/099 Exercise Solution Outlier Removal.mp4
40.4 MB
08 Introduction to Deep Learning [Optional]/053 Training Neural Networks.mp4
40.2 MB
04 A Recommender Engine Framework/022 [Activity] Recommender Engine Walkthrough Part 1.mp4
39.7 MB
09 Deep Learning for Recommender Systems/072 [Activity] Evaluating the RBM Recommender.mp4
39.5 MB
07 Matrix Factorization Methods/045 [Activity] Running SVD and SVD on MovieLens.mp4
39.3 MB
01 Getting Started/006 Top-N Recommender Architecture.mp4
38.9 MB
08 Introduction to Deep Learning [Optional]/050 Deep Learning Pre-Requisites.mp4
38.8 MB
04 A Recommender Engine Framework/024 [Activity] Review the Results of our Algorithm Evaluation..mp4
36.2 MB
06 Neighborhood-Based Collaborative Filtering/032 User-based Collaborative Filtering.mp4
35.9 MB
09 Deep Learning for Recommender Systems/073 [Exercise] Tuning Restricted Boltzmann Machines.mp4
35.2 MB
13 Hybrid Approaches/107 Exercise Solution Hybrid Recommenders.mp4
34.8 MB
04 A Recommender Engine Framework/021 Our Recommender Engine Architecture.mp4
34.3 MB
09 Deep Learning for Recommender Systems/069 Restricted Boltzmann Machines (RBMs).mp4
33.2 MB
08 Introduction to Deep Learning [Optional]/054 Tuning Neural Networks.mp4
32.8 MB
06 Neighborhood-Based Collaborative Filtering/031 Similarity Metrics.mp4
32.2 MB
03 Evaluating Recommender Systems/012 TrainTest and Cross Validation.mp4
30.5 MB
11 Real-World Challenges of Recommender Systems/091 The Cold Start Problem (and solutions).mp4
29.1 MB
09 Deep Learning for Recommender Systems/081 More Emerging Tech to Watch.mp4
29.0 MB
01 Getting Started/003 Course Roadmap.mp4
28.9 MB
12 Case Studies/104 Case Study Netflix Part 1.mp4
28.9 MB
12 Case Studies/102 Case Study YouTube Part 1.mp4
28.2 MB
09 Deep Learning for Recommender Systems/075 Auto-Encoders for Recommendations Deep Learning for Recs.mp4
28.2 MB
01 Getting Started/004 Types of Recommenders.mp4
28.1 MB
06 Neighborhood-Based Collaborative Filtering/035 [Activity] Item-based Collaborative Filtering Hands-On.mp4
28.1 MB
11 Real-World Challenges of Recommender Systems/096 Exercise Solution Implement a Stoplist.mp4
28.0 MB
12 Case Studies/105 Case Study Netflix Part 2.mp4
27.9 MB
07 Matrix Factorization Methods/048 Bleeding Edge Alert Sparse Linear Methods (SLIM).mp4
27.7 MB
12 Case Studies/103 Case Study YouTube Part 2.mp4
27.5 MB
07 Matrix Factorization Methods/044 Singular Value Decomposition.mp4
26.3 MB
06 Neighborhood-Based Collaborative Filtering/039 KNN Recommenders.mp4
26.1 MB
08 Introduction to Deep Learning [Optional]/060 Classifier Patterns with Keras.mp4
26.0 MB
03 Evaluating Recommender Systems/014 Top-N Hit Rate - Many Ways.mp4
25.7 MB
02 Introduction to Python [Optional]/009 Data Structures in Python.mp4
25.6 MB
11 Real-World Challenges of Recommender Systems/093 Exercise Solution Random Exploration.mp4
25.3 MB
05 Content-Based Filtering/029 [Exercise] Dive Deeper into Content-Based Recommendations.mp4
25.3 MB
06 Neighborhood-Based Collaborative Filtering/040 [Activity] Running User and Item-Based KNN on MovieLens.mp4
24.9 MB
07 Matrix Factorization Methods/046 Improving on SVD.mp4
24.2 MB
08 Introduction to Deep Learning [Optional]/063 CNN Architectures.mp4
23.6 MB
03 Evaluating Recommender Systems/020 [Activity] Measure the Performance of SVD Recommendations.mp4
22.6 MB
06 Neighborhood-Based Collaborative Filtering/042 Bleeding Edge Alert Translation-Based Recommendations.mp4
22.5 MB
01 Getting Started/007 [Quiz] Review the basics of recommender systems..mp4
22.3 MB
14 Wrapping Up/109 Bonus Lecture Companion Book and More Courses from Sundog Education.mp4
22.1 MB
08 Introduction to Deep Learning [Optional]/066 Training Recurrent Neural Networks.mp4
21.7 MB
01 Getting Started/005 Understanding You through Implicit and Explicit Ratings.mp4
21.7 MB
11 Real-World Challenges of Recommender Systems/094 Stoplists.mp4
20.9 MB
01 Getting Started/001 Udemy 101 Getting the Most From This Course.mp4
20.7 MB
06 Neighborhood-Based Collaborative Filtering/036 [Exercise] Tuning Collaborative Filtering Algorithms.mp4
20.7 MB
05 Content-Based Filtering/026 K-Nearest-Neighbors and Content Recs.mp4
20.6 MB
13 Hybrid Approaches/106 Hybrid Recommenders and Exercise.mp4
19.3 MB
08 Introduction to Deep Learning [Optional]/049 Deep Learning Introduction.mp4
18.5 MB
10 Scaling it Up/083 Apache Spark Architecture.mp4
18.2 MB
08 Introduction to Deep Learning [Optional]/058 Introduction to Keras.mp4
17.3 MB
10 Scaling it Up/089 AWS SageMaker and Factorization Machines.mp4
16.3 MB
06 Neighborhood-Based Collaborative Filtering/037 [Activity] Evaluating Collaborative Filtering Systems Offline.mp4
16.2 MB
02 Introduction to Python [Optional]/011 [Exercise] Booleans loops and a hands-on challenge.mp4
14.5 MB
03 Evaluating Recommender Systems/015 Coverage Diversity and Novelty.mp4
14.4 MB
03 Evaluating Recommender Systems/017 [Quiz] Review ways to measure your recommender..mp4
13.5 MB
07 Matrix Factorization Methods/047 [Exercise] Tune the hyperparameters on SVD.mp4
13.1 MB
02 Introduction to Python [Optional]/010 Functions in Python.mp4
12.9 MB
09 Deep Learning for Recommender Systems/074 Exercise Results Tuning a RBM Recommender.mp4
12.4 MB
10 Scaling it Up/088 Scaling Up DSSTNE.mp4
10.9 MB
06 Neighborhood-Based Collaborative Filtering/038 [Exercise] Measure the Hit Rate of Item-Based Collaborative Filtering.mp4
10.0 MB
09 Deep Learning for Recommender Systems/078 [Exercise] Get GRU4Rec Working on your Desktop.mp4
7.8 MB
11 Real-World Challenges of Recommender Systems/092 [Exercise] Implement Random Exploration.mp4
2.3 MB
11 Real-World Challenges of Recommender Systems/098 [Exercise] Identify and Eliminate Outlier Users.mp4
1.9 MB
11 Real-World Challenges of Recommender Systems/095 [Exercise] Implement a Stoplist.mp4
1.4 MB
08 Introduction to Deep Learning [Optional]/056 [Activity] Handwriting Recognition with Tensorflow part 1-en.srt
34.1 kB
08 Introduction to Deep Learning [Optional]/055 Introduction to Tensorflow-en.srt
26.6 kB
09 Deep Learning for Recommender Systems/070 [Activity] Recommendations with RBMs part 1-en.srt
25.7 kB
08 Introduction to Deep Learning [Optional]/052 [Activity] Playing with Tensorflow-en.srt
23.8 kB
08 Introduction to Deep Learning [Optional]/067 [Activity] Sentiment Analysis of Movie Reviews using RNNs and Keras-en.srt
23.2 kB
08 Introduction to Deep Learning [Optional]/051 History of Artificial Neural Networks-en.srt
23.0 kB
08 Introduction to Deep Learning [Optional]/059 [Activity] Handwriting Recognition with Keras-en.srt
20.1 kB
06 Neighborhood-Based Collaborative Filtering/031 Similarity Metrics-en.srt
19.3 kB
08 Introduction to Deep Learning [Optional]/062 Intro to Convolutional Neural Networks (CNNs)-en.srt
18.4 kB
08 Introduction to Deep Learning [Optional]/061 [Exercise] Predict Political Parties of Politicians with Keras-en.srt
18.3 kB
08 Introduction to Deep Learning [Optional]/050 Deep Learning Pre-Requisites-en.srt
18.3 kB
05 Content-Based Filtering/025 Content-Based Recommendations and the Cosine Similarity Metric-en.srt
18.3 kB
08 Introduction to Deep Learning [Optional]/064 [Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs)-en.srt
17.2 kB
09 Deep Learning for Recommender Systems/079 Exercise Results GRU4Rec in Action-en.srt
16.7 kB
09 Deep Learning for Recommender Systems/069 Restricted Boltzmann Machines (RBMs)-en.srt
16.6 kB
08 Introduction to Deep Learning [Optional]/065 Intro to Recurrent Neural Networks (RNNs)-en.srt
15.9 kB
01 Getting Started/002 [Activity] Install Anaconda course materials and create movie recommendations-en.srt
15.6 kB
09 Deep Learning for Recommender Systems/077 Clickstream Recommendations with RNNs-en.srt
15.5 kB
04 A Recommender Engine Framework/021 Our Recommender Engine Architecture-en.srt
15.2 kB
06 Neighborhood-Based Collaborative Filtering/032 User-based Collaborative Filtering-en.srt
14.6 kB
12 Case Studies/103 Case Study YouTube Part 2-en.srt
14.6 kB
09 Deep Learning for Recommender Systems/071 [Activity] Recommendations with RBMs part 2-en.srt
14.4 kB
07 Matrix Factorization Methods/043 Principal Component Analysis (PCA)-en.srt
14.4 kB
07 Matrix Factorization Methods/044 Singular Value Decomposition-en.srt
13.9 kB
08 Introduction to Deep Learning [Optional]/057 [Activity] Handwriting Recognition with Tensorflow part 2-en.srt
13.7 kB
09 Deep Learning for Recommender Systems/076 [Activity] Recommendations with Deep Neural Networks-en.srt
13.7 kB
11 Real-World Challenges of Recommender Systems/091 The Cold Start Problem (and solutions)-en.srt
13.6 kB
10 Scaling it Up/090 SageMaker in Action Factorization Machines on one million ratings in the cloud-en.srt
13.2 kB
03 Evaluating Recommender Systems/018 [Activity] Walkthrough of RecommenderMetrics.py-en.srt
13.1 kB
08 Introduction to Deep Learning [Optional]/053 Training Neural Networks-en.srt
12.8 kB
11 Real-World Challenges of Recommender Systems/097 Filter Bubbles Trust and Outliers-en.srt
12.4 kB
10 Scaling it Up/087 DSSTNE in Action-en.srt
11.9 kB
01 Getting Started/006 Top-N Recommender Architecture-en.srt
11.9 kB
09 Deep Learning for Recommender Systems/080 Bleeding Edge Alert Deep Factorization Machines-en.srt
11.7 kB
10 Scaling it Up/084 [Activity] Movie Recommendations with Spark Matrix Factorization and ALS-en.srt
11.4 kB
03 Evaluating Recommender Systems/016 Churn Responsiveness and AB Tests-en.srt
11.2 kB
06 Neighborhood-Based Collaborative Filtering/030 Measuring Similarity and Sparsity-en.srt
11.0 kB
03 Evaluating Recommender Systems/019 [Activity] Walkthrough of TestMetrics.py-en.srt
10.9 kB
09 Deep Learning for Recommender Systems/081 More Emerging Tech to Watch-en.srt
10.8 kB
03 Evaluating Recommender Systems/015 Coverage Diversity and Novelty-en.srt
10.8 kB
05 Content-Based Filtering/027 [Activity] Producing and Evaluating Content-Based Movie Recommendations-en.srt
10.6 kB
11 Real-World Challenges of Recommender Systems/094 Stoplists-en.srt
10.5 kB
10 Scaling it Up/083 Apache Spark Architecture-en.srt
10.5 kB
11 Real-World Challenges of Recommender Systems/100 Fraud The Perils of Clickstream and International Concerns-en.srt
9.9 kB
06 Neighborhood-Based Collaborative Filtering/033 [Activity] User-based Collaborative Filtering Hands-On-en.srt
9.8 kB
02 Introduction to Python [Optional]/009 Data Structures in Python-en.srt
9.7 kB
09 Deep Learning for Recommender Systems/075 Auto-Encoders for Recommendations Deep Learning for Recs-en.srt
9.6 kB
10 Scaling it Up/086 Amazon DSSTNE-en.srt
9.4 kB
03 Evaluating Recommender Systems/014 Top-N Hit Rate - Many Ways-en.srt
9.4 kB
07 Matrix Factorization Methods/046 Improving on SVD-en.srt
9.3 kB
01 Getting Started/007 [Quiz] Review the basics of recommender systems.-en.srt
9.1 kB
06 Neighborhood-Based Collaborative Filtering/034 Item-based Collaborative Filtering-en.srt
9.0 kB
06 Neighborhood-Based Collaborative Filtering/041 [Exercise] Experiment with different KNN parameters.-en.srt
9.0 kB
01 Getting Started/005 Understanding You through Implicit and Explicit Ratings-en.srt
9.0 kB
02 Introduction to Python [Optional]/008 [Activity] The Basics of Python-en.srt
8.9 kB
05 Content-Based Filtering/028 [Activity] Bleeding Edge Alert Mise en Scene Recommendations-en.srt
8.8 kB
05 Content-Based Filtering/029 [Exercise] Dive Deeper into Content-Based Recommendations-en.srt
8.7 kB
03 Evaluating Recommender Systems/013 Accuracy Metrics (RMSE MAE)-en.srt
8.7 kB
10 Scaling it Up/089 AWS SageMaker and Factorization Machines-en.srt
8.6 kB
10 Scaling it Up/085 [Activity] Recommendations from 20 million ratings with Spark-en.srt
8.6 kB
13 Hybrid Approaches/107 Exercise Solution Hybrid Recommenders-en.srt
8.5 kB
03 Evaluating Recommender Systems/012 TrainTest and Cross Validation-en.srt
8.5 kB
01 Getting Started/003 Course Roadmap-en.srt
8.5 kB
08 Introduction to Deep Learning [Optional]/054 Tuning Neural Networks-en.srt
8.5 kB
06 Neighborhood-Based Collaborative Filtering/039 KNN Recommenders-en.srt
8.4 kB
10 Scaling it Up/082 [Activity] Introduction and Installation of Apache Spark-en.srt
8.4 kB
05 Content-Based Filtering/026 K-Nearest-Neighbors and Content Recs-en.srt
8.3 kB
08 Introduction to Deep Learning [Optional]/060 Classifier Patterns with Keras-en.srt
8.2 kB
04 A Recommender Engine Framework/023 [Activity] Recommender Engine Walkthrough Part 2-en.srt
8.1 kB
12 Case Studies/104 Case Study Netflix Part 1-en.srt
7.8 kB
12 Case Studies/105 Case Study Netflix Part 2-en.srt
7.8 kB
07 Matrix Factorization Methods/048 Bleeding Edge Alert Sparse Linear Methods (SLIM)-en.srt
7.7 kB
11 Real-World Challenges of Recommender Systems/099 Exercise Solution Outlier Removal-en.srt
7.7 kB
11 Real-World Challenges of Recommender Systems/101 Temporal Effects and Value-Aware Recommendations-en.srt
7.7 kB
04 A Recommender Engine Framework/022 [Activity] Recommender Engine Walkthrough Part 1-en.srt
7.6 kB
12 Case Studies/102 Case Study YouTube Part 1-en.srt
7.4 kB
06 Neighborhood-Based Collaborative Filtering/036 [Exercise] Tuning Collaborative Filtering Algorithms-en.srt
7.1 kB
01 Getting Started/004 Types of Recommenders-en.srt
6.8 kB
09 Deep Learning for Recommender Systems/072 [Activity] Evaluating the RBM Recommender-en.srt
6.8 kB
08 Introduction to Deep Learning [Optional]/066 Training Recurrent Neural Networks-en.srt
6.8 kB
07 Matrix Factorization Methods/045 [Activity] Running SVD and SVD on MovieLens-en.srt
6.5 kB
04 A Recommender Engine Framework/024 [Activity] Review the Results of our Algorithm Evaluation.-en.srt
6.5 kB
02 Introduction to Python [Optional]/011 [Exercise] Booleans loops and a hands-on challenge-en.srt
6.4 kB
08 Introduction to Deep Learning [Optional]/063 CNN Architectures-en.srt
6.4 kB
08 Introduction to Deep Learning [Optional]/058 Introduction to Keras-en.srt
6.3 kB
13 Hybrid Approaches/106 Hybrid Recommenders and Exercise-en.srt
5.6 kB
03 Evaluating Recommender Systems/017 [Quiz] Review ways to measure your recommender.-en.srt
5.6 kB
09 Deep Learning for Recommender Systems/078 [Exercise] Get GRU4Rec Working on your Desktop-en.srt
5.4 kB
02 Introduction to Python [Optional]/010 Functions in Python-en.srt
5.3 kB
03 Evaluating Recommender Systems/020 [Activity] Measure the Performance of SVD Recommendations-en.srt
5.1 kB
14 Wrapping Up/108 More to Explore-en.srt
5.1 kB
06 Neighborhood-Based Collaborative Filtering/042 Bleeding Edge Alert Translation-Based Recommendations-en.srt
5.0 kB
06 Neighborhood-Based Collaborative Filtering/035 [Activity] Item-based Collaborative Filtering Hands-On-en.srt
5.0 kB
09 Deep Learning for Recommender Systems/068 Intro to Deep Learning for Recommenders-en.srt
4.9 kB
06 Neighborhood-Based Collaborative Filtering/040 [Activity] Running User and Item-Based KNN on MovieLens-en.srt
4.8 kB
06 Neighborhood-Based Collaborative Filtering/038 [Exercise] Measure the Hit Rate of Item-Based Collaborative Filtering-en.srt
4.6 kB
11 Real-World Challenges of Recommender Systems/096 Exercise Solution Implement a Stoplist-en.srt
4.4 kB
10 Scaling it Up/088 Scaling Up DSSTNE-en.srt
4.3 kB
11 Real-World Challenges of Recommender Systems/093 Exercise Solution Random Exploration-en.srt
4.3 kB
07 Matrix Factorization Methods/047 [Exercise] Tune the hyperparameters on SVD-en.srt
4.1 kB
01 Getting Started/001 Udemy 101 Getting the Most From This Course-en.srt
4.0 kB
09 Deep Learning for Recommender Systems/073 [Exercise] Tuning Restricted Boltzmann Machines-en.srt
3.9 kB
08 Introduction to Deep Learning [Optional]/049 Deep Learning Introduction-en.srt
3.4 kB
06 Neighborhood-Based Collaborative Filtering/037 [Activity] Evaluating Collaborative Filtering Systems Offline-en.srt
2.6 kB
09 Deep Learning for Recommender Systems/074 Exercise Results Tuning a RBM Recommender-en.srt
2.5 kB
11 Real-World Challenges of Recommender Systems/092 [Exercise] Implement Random Exploration-en.srt
1.8 kB
14 Wrapping Up/109 Bonus Lecture Companion Book and More Courses from Sundog Education-en.srt
1.7 kB
11 Real-World Challenges of Recommender Systems/098 [Exercise] Identify and Eliminate Outlier Users-en.srt
1.7 kB
11 Real-World Challenges of Recommender Systems/095 [Exercise] Implement a Stoplist-en.srt
1.2 kB
[FCS Forum].url
133 Bytes
[FreeCourseSite.com].url
127 Bytes
[CourseClub.NET].url
123 Bytes
14 Wrapping Up/109 Sundog-Education-website.txt
35 Bytes
14 Wrapping Up/109 Building-Recommender-Systems-book-on-Amazon.txt
23 Bytes
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MARCH-200
CETD-097
SEND-160
ISO-655
UGUG-028
DSE-814
SICP-101
YOGU-002
WNID-003
NATR-264
HHK-019
KICJ-830
TMSG-018
DDN-165
DANDY-038
ADZ-126
ZACK-008
ASFB-195
DUAL-201
VEC-022
ATP-250
VSPDS-464
MDLD-121
AOSBD-007
EMU-007
EMU-033
SDMS-187
DBEB-024
SDMS-471
GOTHIC-015
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