[CourseClub.NET] Packtpub - Building Recommender Systems with Machine Learning and AI torrent, magnet, bt

Latest Search: 1.aCosta 2.GIO15 3.inked girls 4.ROE 273 5.東京攻略01

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

magnet:?xt=urn:btih:333A3D99C556019529A3D9CA01FD159B5894792B&dn=%5BCourseClub.NET%5D%20Packtpub%20-%20Building%20Recommender%20Systems%20with%20Machine%20Learning%20and%20AI

QR Code Copy to Clipboard Open with BT Client

Torrent Hash:

333A3D99C556019529A3D9CA01FD159B5894792B

Number of Files:

110

Content Size:

2.89GB

Convert On:

2018-09-28

Keywords:

CourseClub NET Packtpub Building Recommender Systems with Machine Learning and AI

Magnet Link:

magnet:?xt=urn:btih:333A3D99C556019529A3D9CA01FD159B5894792B&dn=%5BCourseClub.NET%5D%20Packtpub%20-%20Building%20Recommender%20Systems%20with%20Machine%20Learning%20and%20AI

Link:

//btsow.motorcycles/magnet/detail/hash/333A3D99C556019529A3D9CA01FD159B5894792B

Download

Play Now

File Name

Size

01.Getting Started/0101.Install Anaconda, course materials, and create movie recommendations!.mp4

88.13MB

01.Getting Started/0102.Course Roadmap.mp4

69.27MB

01.Getting Started/0103.Types of Recommenders.mp4

14.11MB

01.Getting Started/0104.Understanding You through Implicit and Explicit Ratings.mp4

9.2MB

01.Getting Started/0105.Top-N Recommender Architecture.mp4

15.32MB

01.Getting Started/0106.Review the basics of recommender systems..mp4

11.16MB

02.Introduction to Python/0201.The Basics of Python.mp4

42MB

02.Introduction to Python/0202.Data Structures in Python.mp4

11.59MB

02.Introduction to Python/0203.Functions in Python.mp4

5.85MB

02.Introduction to Python/0204.Booleans, loops, and a hands-on challenge.mp4

7.33MB

03.Evaluating Recommender Systems/0301.TrainTest and Cross Validation.mp4

23.17MB

03.Evaluating Recommender Systems/0302.Accuracy Metrics (RMSE, MAE).mp4

46.73MB

03.Evaluating Recommender Systems/0303.Top-N Hit Rate - Many Ways.mp4

12.16MB

03.Evaluating Recommender Systems/0304.Coverage, Diversity, and Novelty.mp4

7.94MB

03.Evaluating Recommender Systems/0305.Churn, Responsiveness, and AB Tests.mp4

82.68MB

03.Evaluating Recommender Systems/0306.Review ways to measure your recommender..mp4

8.26MB

03.Evaluating Recommender Systems/0307.Walkthrough of RecommenderMetrics.py.mp4

38.78MB

03.Evaluating Recommender Systems/0308.Walkthrough of TestMetrics.py.mp4

25.34MB

03.Evaluating Recommender Systems/0309.Measure the Performance of SVD Recommendations.mp4

12.05MB

04.A Recommender Engine Framework/0401.Our Recommender Engine Architecture.mp4

18.17MB

04.A Recommender Engine Framework/0402.Recommender Engine Walkthrough, Part 1.mp4

18.55MB

04.A Recommender Engine Framework/0403.Recommender Engine Walkthrough, Part 2.mp4

18.57MB

04.A Recommender Engine Framework/0404.Review the Results of our Algorithm Evaluation..mp4

14.3MB

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

38.47MB

05.Content-Based Filtering/0502.K-Nearest-Neighbors and Content Recs.mp4

11.84MB

05.Content-Based Filtering/0503.Producing and Evaluating Content-Based Movie Recommendations.mp4

27.89MB

05.Content-Based Filtering/0504.Bleeding Edge Alert! Mise en Scene Recommendations.mp4

33.71MB

05.Content-Based Filtering/0505.Dive Deeper into Content-Based Recommendations.mp4

10.66MB

06.Neighborhood-Based Collaborative Filtering/0601.Measuring Similarity, and Sparsity.mp4

69.75MB

06.Neighborhood-Based Collaborative Filtering/0602.Similarity Metrics.mp4

15.45MB

06.Neighborhood-Based Collaborative Filtering/0603.User-based Collaborative Filtering.mp4

19.99MB

06.Neighborhood-Based Collaborative Filtering/0604.User-based Collaborative Filtering, Hands-On.mp4

24.56MB

06.Neighborhood-Based Collaborative Filtering/0605.Item-based Collaborative Filtering.mp4

61.59MB

06.Neighborhood-Based Collaborative Filtering/0606.Item-based Collaborative Filtering, Hands-On.mp4

18.12MB

06.Neighborhood-Based Collaborative Filtering/0607.Tuning Collaborative Filtering Algorithms.mp4

10.06MB

06.Neighborhood-Based Collaborative Filtering/0608.Evaluating Collaborative Filtering Systems Offline.mp4

10.57MB

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

4.43MB

06.Neighborhood-Based Collaborative Filtering/0610.KNN Recommenders.mp4

21.88MB

06.Neighborhood-Based Collaborative Filtering/0611.Running User and Item-Based KNN on MovieLens.mp4

19.63MB

06.Neighborhood-Based Collaborative Filtering/0612.Experiment with different KNN parameters..mp4

38.78MB

06.Neighborhood-Based Collaborative Filtering/0613.Bleeding Edge Alert! Translation-Based Recommendations.mp4

19.64MB

07.Matrix Factorization Methods/0701.Principal Component Analysis (PCA).mp4

64.98MB

07.Matrix Factorization Methods/0702.Singular Value Decomposition.mp4

12.98MB

07.Matrix Factorization Methods/0703.Running SVD and SVD++ on MovieLens.mp4

23.12MB

07.Matrix Factorization Methods/0704.Improving on SVD.mp4

9.69MB

07.Matrix Factorization Methods/0705.Tune the hyperparameters on SVD.mp4

8.02MB

07.Matrix Factorization Methods/0706.Bleeding Edge Alert! Sparse Linear Methods (SLIM).mp4

21.08MB

08.Introduction to Deep Learning/0801.Deep Learning Introduction.mp4

22.8MB

08.Introduction to Deep Learning/0802.Deep Learning Pre-Requisites.mp4

20.12MB

08.Introduction to Deep Learning/0803.History of Artificial Neural Networks.mp4

40.44MB

08.Introduction to Deep Learning/0804.[Activity] Playing with Tensorflow.mp4

116.91MB

08.Introduction to Deep Learning/0805.Training Neural Networks.mp4

18.84MB

08.Introduction to Deep Learning/0806.Tuning Neural Networks.mp4

13.11MB

08.Introduction to Deep Learning/0807.Introduction to Tensorflow.mp4

43MB

08.Introduction to Deep Learning/0808.[Activity] Handwriting Recognition with Tensorflow, part 1.mp4

92.89MB

08.Introduction to Deep Learning/0809.[Activity] Handwriting Recognition with Tensorflow, part 2.mp4

27.4MB

08.Introduction to Deep Learning/0810.Introduction to Keras.mp4

6.67MB

08.Introduction to Deep Learning/0811.[Activity] Handwriting Recognition with Keras.mp4

46.94MB

08.Introduction to Deep Learning/0812.Classifier Patterns with Keras.mp4

13.12MB

08.Introduction to Deep Learning/0813.[Exercise] Predict Political Parties of Politicians with Keras.mp4

53.7MB

08.Introduction to Deep Learning/0814.Intro to Convolutional Neural Networks (CNN_s).mp4

36.4MB

08.Introduction to Deep Learning/0815.CNN Architectures.mp4

9.65MB

08.Introduction to Deep Learning/0816.[Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs).mp4

42.41MB

08.Introduction to Deep Learning/0817.Intro to Recurrent Neural Networks (RNN_s).mp4

22.49MB

08.Introduction to Deep Learning/0818.Training Recurrent Neural Networks.mp4

10.1MB

08.Introduction to Deep Learning/0819.[Activity] Sentiment Analysis of Movie Reviews using RNN_s and Keras.mp4

73.37MB

09.Deep Learning for Recommender Systems/0901.Intro to Deep Learning for Recommenders.mp4

55.99MB

09.Deep Learning for Recommender Systems/0902.Restricted Boltzmann Machines (RBM_s).mp4

15.93MB

09.Deep Learning for Recommender Systems/0903.[Activity] Recommendations with RBM_s, part 1.mp4

50.52MB

09.Deep Learning for Recommender Systems/0904.[Activity] Recommendations with RBM_s, part 2.mp4

26.41MB

09.Deep Learning for Recommender Systems/0905.[Activity] Evaluating the RBM Recommender.mp4

19.85MB

09.Deep Learning for Recommender Systems/0906.[Exercise] Tuning Restricted Boltzmann Machines.mp4

53.71MB

09.Deep Learning for Recommender Systems/0907.Exercise Results Tuning a RBM Recommender.mp4

6.63MB

09.Deep Learning for Recommender Systems/0908.Auto-Encoders for Recommendations Deep Learning for Recs.mp4

11.82MB

09.Deep Learning for Recommender Systems/0909.[Activity] Recommendations with Deep Neural Networks.mp4

37.22MB

09.Deep Learning for Recommender Systems/0910.Clickstream Recommendations with RNN_s.mp4

24.84MB

09.Deep Learning for Recommender Systems/0911.[Exercise] Get GRU4Rec Working on your Desktop.mp4

3.88MB

09.Deep Learning for Recommender Systems/0912.Exercise Results GRU4Rec in Action.mp4

41.06MB

09.Deep Learning for Recommender Systems/0913.Bleeding Edge Alert! Deep Factorization Machines.mp4

44.31MB

09.Deep Learning for Recommender Systems/0914.More Emerging Tech to Watch.mp4

14.16MB

10.Scaling it up/1001.[Activity] Introduction and Installation of Apache Spark.mp4

40.04MB

10.Scaling it up/1002.Apache Spark Architecture.mp4

9.37MB

10.Scaling it up/1003.[Activity] Movie Recommendations with Spark, Matrix Factorization, and ALS.mp4

23.76MB

10.Scaling it up/1004.[Activity] Recommendations from 20 million ratings with Spark.mp4

26.92MB

10.Scaling it up/1005.Amazon DSSTNE.mp4

41.35MB

10.Scaling it up/1006.DSSTNE in Action.mp4

61.12MB

10.Scaling it up/1007.Scaling Up DSSTNE.mp4

4.82MB

10.Scaling it up/1008.AWS SageMaker and Factorization Machines.mp4

7.95MB

10.Scaling it up/1009.SageMaker in Action Factorization Machines on one million ratings, in the cloud.mp4

44.2MB

11.11 Real-World Challenges of Recommender Systems/1101.The Cold Start Problem (and solutions).mp4

11.8MB

11.11 Real-World Challenges of Recommender Systems/1102.[Exercise] Implement Random Exploration.mp4

1.19MB

11.11 Real-World Challenges of Recommender Systems/1103.Exercise Solution Random Exploration.mp4

15.43MB

11.11 Real-World Challenges of Recommender Systems/1104.Stoplists.mp4

8.67MB

11.11 Real-World Challenges of Recommender Systems/1105.[Exercise] Implement a Stoplist.mp4

761.82KB

11.11 Real-World Challenges of Recommender Systems/1106.Exercise Solution Implement a Stoplist.mp4

15.07MB

11.11 Real-World Challenges of Recommender Systems/1107.Filter Bubbles, Trust, and Outliers.mp4

21.76MB

11.11 Real-World Challenges of Recommender Systems/1108.[Exercise] Identify and Eliminate Outlier Users.mp4

1020.31KB

11.11 Real-World Challenges of Recommender Systems/1109.Exercise Solution Outlier Removal.mp4

16.61MB

11.11 Real-World Challenges of Recommender Systems/1110.Fraud, the Perils of Clickstream, and International Concerns.mp4

72.79MB

11.11 Real-World Challenges of Recommender Systems/1111.Temporal Effects, and Value-Aware Recommendations.mp4

81.63MB

12.Case Studies/1201.Case Study YouTube, Part 1.mp4

12.79MB

12.Case Studies/1202.Case Study YouTube, Part 2.mp4

12.47MB

12.Case Studies/1203.Case Study Netflix, Part 1.mp4

13.85MB

12.Case Studies/1204.Case Study Netflix, Part 2.mp4

9.84MB

13.Hybrid Approaches/1301.Hybrid Recommenders and Exercise.mp4

8.82MB

13.Hybrid Approaches/1302.Exercise Solution Hybrid Recommenders.mp4

20.42MB

14.Wrapping Up/1401.More to Explore.mp4

61.91MB

Exercise Files/exercise_files.zip

1.7MB

[CourseClub.NET].url

123B

[DesireCourse.Com].url

51B

Latest Search:

1.aCosta 2.GIO15 3.inked girls 4.ROE 273 5.東京攻略01 6.mimk-170 7.mih16386 8.group xxx 9.Urban Gypsy 10.MIUM-1116 11. SSNI-826 12. ABF-181 13.TRP-035 14.MilfVR Duchess Of Pork 15.91PCM-001 16.75353 17.4585594 18.ssis570 19.ntr 035 20.kaden 21.cawd355 22.S59E221 23.Pirates 24.HDKA-314 25.oopsfamily 26.jukujo7285 27.Kay.Lovely.07 20 28.ppv-3253595 29.MIUM295 30.Jukujo7604