Building Recommender Systems with Machine Learning and AI | 6AF7C6CCE09FADC67BBCBF7A931E1DB8C6142A62

Building Recommender Systems with Machine Learning and AI

Name	Building Recommender Systems with Machine Learning and AI	DOWNLOAD Copy Link
Total Size	4.8 GB
Total Files	223
Hash	6AF7C6CCE09FADC67BBCBF7A931E1DB8C6142A62

/.../8. Introduction to Deep Learning [Optional]/
4. [Activity] Playing with Tensorflow.mp4	152.6 MB
1. Deep Learning Introduction.mp4	18.5 MB
1. Deep Learning Introduction.srt	3.7 KB
2. Deep Learning Pre-Requisites.mp4	38.8 MB
2. Deep Learning Pre-Requisites.srt	20.1 KB
3. History of Artificial Neural Networks.mp4	88.3 MB
3. History of Artificial Neural Networks.srt	25.4 KB
4. [Activity] Playing with Tensorflow.srt	25.5 KB
5. Training Neural Networks.mp4	40.2 MB
5. Training Neural Networks.srt	14.1 KB
6. Tuning Neural Networks.mp4	32.5 MB
6. Tuning Neural Networks.srt	9.1 KB
7. Introduction to Tensorflow.mp4	97.0 MB
7. Introduction to Tensorflow.srt	29.4 KB
8. [Activity] Handwriting Recognition with Tensorflow, part 1.mp4	95.4 MB
8. [Activity] Handwriting Recognition with Tensorflow, part 1.srt	17.3 KB
9. [Activity] Handwriting Recognition with Tensorflow, part 2.mp4	95.3 MB
9. [Activity] Handwriting Recognition with Tensorflow, part 2.srt	20.3 KB
10. [Activity] Handwriting Recognition with Tensorflow, Part 3.mp4	52.8 MB
10. [Activity] Handwriting Recognition with Tensorflow, Part 3.srt	13.8 KB
11. Introduction to Keras.mp4	17.3 MB
11. Introduction to Keras.srt	7.0 KB
12. [Activity] Handwriting Recognition with Keras.mp4	92.8 MB
12. [Activity] Handwriting Recognition with Keras.srt	21.8 KB
13. Classifier Patterns with Keras.mp4	26.0 MB
13. Classifier Patterns with Keras.srt	9.0 KB
14. [Exercise] Predict Political Parties of Politicians with Keras.mp4	105.1 MB
14. [Exercise] Predict Political Parties of Politicians with Keras.srt	20.2 KB
15. Intro to Convolutional Neural Networks (CNN's).mp4	82.0 MB
15. Intro to Convolutional Neural Networks (CNN's).srt	20.2 KB
16. CNN Architectures.mp4	23.6 MB
16. CNN Architectures.srt	7.1 KB
17. [Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs).mp4	86.3 MB
17. [Activity] Handwriting Recognition with Convolutional Neural Networks (CNNs).srt	18.9 KB
18. Intro to Recurrent Neural Networks (RNN's).mp4	52.1 MB
18. Intro to Recurrent Neural Networks (RNN's).srt	17.6 KB
19. Training Recurrent Neural Networks.mp4	21.7 MB
19. Training Recurrent Neural Networks.srt	7.4 KB
20. [Activity] Sentiment Analysis of Movie Reviews using RNN's and Keras.mp4	125.6 MB
20. [Activity] Sentiment Analysis of Movie Reviews using RNN's and Keras.srt	25.7 KB
/
Visit Coursedrive.org.url	0.1 KB
ReadMe.txt	0.2 KB
/Building Recommender Systems with Machine Learning and AI/
ReadMe.txt	0.2 KB
Visit Coursedrive.org.url	0.1 KB
/1. Getting Started/
1. Udemy 101 Getting the Most From This Course.mp4	20.7 MB
1. Udemy 101 Getting the Most From This Course.srt	4.1 KB
2. [Activity] Install Anaconda, course materials, and create movie recommendations!.mp4	109.1 MB
2. [Activity] Install Anaconda, course materials, and create movie recommendations!.srt	17.5 KB
3. Course Roadmap.mp4	28.9 MB
3. Course Roadmap.srt	10.1 KB
4. Types of Recommenders.mp4	28.1 MB
4. Types of Recommenders.srt	7.5 KB
5. Understanding You through Implicit and Explicit Ratings.mp4	21.7 MB
5. Understanding You through Implicit and Explicit Ratings.srt	9.8 KB
6. Top-N Recommender Architecture.mp4	38.9 MB
6. Top-N Recommender Architecture.srt	13.1 KB
7. [Quiz] Review the basics of recommender systems..mp4	22.3 MB
7. [Quiz] Review the basics of recommender systems..srt	10.1 KB
/.../2. Introduction to Python [Optional]/
1. [Activity] The Basics of Python.mp4	45.1 MB
1. [Activity] The Basics of Python.srt	9.8 KB
2. Data Structures in Python.mp4	25.6 MB
2. Data Structures in Python.srt	10.7 KB
3. Functions in Python.mp4	12.9 MB
3. Functions in Python.srt	5.8 KB
4. [Exercise] Booleans, loops, and a hands-on challenge.mp4	14.5 MB
4. [Exercise] Booleans, loops, and a hands-on challenge.srt	7.0 KB
/.../3. Evaluating Recommender Systems/
1. TrainTest and Cross Validation.mp4	30.5 MB
1. TrainTest and Cross Validation.srt	9.5 KB
2. Accuracy Metrics (RMSE, MAE).mp4	42.2 MB
2. Accuracy Metrics (RMSE, MAE).srt	9.5 KB
3. Top-N Hit Rate - Many Ways.mp4	25.7 MB
3. Top-N Hit Rate - Many Ways.srt	10.4 KB
4. Coverage, Diversity, and Novelty.mp4	14.4 MB
4. Coverage, Diversity, and Novelty.srt	12.2 KB
5. Churn, Responsiveness, and AB Tests.mp4	63.9 MB
5. Churn, Responsiveness, and AB Tests.srt	12.4 KB
6. [Quiz] Review ways to measure your recommender..mp4	13.5 MB
6. [Quiz] Review ways to measure your recommender..srt	6.2 KB
7. [Activity] Walkthrough of RecommenderMetrics.py.mp4	67.4 MB
7. [Activity] Walkthrough of RecommenderMetrics.py.srt	14.5 KB
8. [Activity] Walkthrough of TestMetrics.py.mp4	57.0 MB
8. [Activity] Walkthrough of TestMetrics.py.srt	12.1 KB
9. [Activity] Measure the Performance of SVD Recommendations.mp4	22.6 MB
9. [Activity] Measure the Performance of SVD Recommendations.srt	5.7 KB
/.../4. A Recommender Engine Framework/
1. Our Recommender Engine Architecture.mp4	34.3 MB
1. Our Recommender Engine Architecture.srt	16.7 KB
2. [Activity] Recommender Engine Walkthrough, Part 1.mp4	39.7 MB
2. [Activity] Recommender Engine Walkthrough, Part 1.srt	8.3 KB
3. [Activity] Recommender Engine Walkthrough, Part 2.mp4	41.5 MB
3. [Activity] Recommender Engine Walkthrough, Part 2.srt	8.9 KB
4. [Activity] Review the Results of our Algorithm Evaluation..mp4	36.2 MB
4. [Activity] Review the Results of our Algorithm Evaluation..srt	7.1 KB
/.../5. Content-Based Filtering/
1. Content-Based Recommendations, and the Cosine Similarity Metric.mp4	64.6 MB
1. Content-Based Recommendations, and the Cosine Similarity Metric.srt	20.3 KB
2. K-Nearest-Neighbors and Content Recs.mp4	20.6 MB
2. K-Nearest-Neighbors and Content Recs.srt	9.1 KB
3. [Activity] Producing and Evaluating Content-Based Movie Recommendations.mp4	54.9 MB
3. [Activity] Producing and Evaluating Content-Based Movie Recommendations.srt	11.7 KB
4. [Activity] Bleeding Edge Alert! Mise en Scene Recommendations.mp4	48.8 MB
4. [Activity] Bleeding Edge Alert! Mise en Scene Recommendations.srt	9.7 KB
5. [Exercise] Dive Deeper into Content-Based Recommendations.mp4	25.3 MB
5. [Exercise] Dive Deeper into Content-Based Recommendations.srt	9.5 KB
/.../6. Neighborhood-Based Collaborative Filtering/
1. Measuring Similarity, and Sparsity.mp4	62.0 MB
1. Measuring Similarity, and Sparsity.srt	12.3 KB
2. Similarity Metrics.mp4	32.2 MB
2. Similarity Metrics.srt	21.4 KB
3. User-based Collaborative Filtering.mp4	35.9 MB
3. User-based Collaborative Filtering.srt	16.0 KB
4. [Activity] User-based Collaborative Filtering, Hands-On.mp4	51.0 MB
4. [Activity] User-based Collaborative Filtering, Hands-On.srt	10.9 KB
5. Item-based Collaborative Filtering.mp4	54.8 MB
5. Item-based Collaborative Filtering.srt	10.2 KB
6. [Activity] Item-based Collaborative Filtering, Hands-On.mp4	28.1 MB
6. [Activity] Item-based Collaborative Filtering, Hands-On.srt	5.5 KB
7. [Exercise] Tuning Collaborative Filtering Algorithms.mp4	20.7 MB
7. [Exercise] Tuning Collaborative Filtering Algorithms.srt	7.8 KB
8. [Activity] Evaluating Collaborative Filtering Systems Offline.mp4	16.2 MB
8. [Activity] Evaluating Collaborative Filtering Systems Offline.srt	2.9 KB
9. [Exercise] Measure the Hit Rate of Item-Based Collaborative Filtering.mp4	10.0 MB
9. [Exercise] Measure the Hit Rate of Item-Based Collaborative Filtering.srt	5.0 KB
10. KNN Recommenders.mp4	26.1 MB
10. KNN Recommenders.srt	9.3 KB
11. [Activity] Running User and Item-Based KNN on MovieLens.mp4	24.9 MB
11. [Activity] Running User and Item-Based KNN on MovieLens.srt	5.2 KB
12. [Exercise] Experiment with different KNN parameters..mp4	43.3 MB
12. [Exercise] Experiment with different KNN parameters..srt	9.9 KB
13. Bleeding Edge Alert! Translation-Based Recommendations.mp4	22.3 MB
13. Bleeding Edge Alert! Translation-Based Recommendations.srt	5.4 KB
/.../7. Matrix Factorization Methods/
1. Principal Component Analysis (PCA).mp4	64.2 MB
1. Principal Component Analysis (PCA).srt	16.0 KB
2. Singular Value Decomposition.mp4	25.5 MB
2. Singular Value Decomposition.srt	14.7 KB
3. [Activity] Running SVD and SVD++ on MovieLens.mp4	39.3 MB
3. [Activity] Running SVD and SVD++ on MovieLens.srt	7.2 KB
4. Improving on SVD.mp4	24.2 MB
4. Improving on SVD.srt	10.2 KB
5. [Exercise] Tune the hyperparameters on SVD.mp4	12.4 MB
5. [Exercise] Tune the hyperparameters on SVD.srt	4.5 KB
6. Bleeding Edge Alert! Sparse Linear Methods (SLIM).mp4	27.8 MB
6. Bleeding Edge Alert! Sparse Linear Methods (SLIM).srt	8.0 KB
/.../9. Deep Learning for Recommender Systems/
1. Intro to Deep Learning for Recommenders.mp4	44.7 MB
1. Intro to Deep Learning for Recommenders.srt	5.4 KB
2. Restricted Boltzmann Machines (RBM's).mp4	33.2 MB
2. Restricted Boltzmann Machines (RBM's).srt	18.5 KB
3. [Activity] Recommendations with RBM's, part 1.mp4	151.5 MB
3. [Activity] Recommendations with RBM's, part 1.srt	28.4 KB
4. [Activity] Recommendations with RBM's, part 2.mp4	80.5 MB
4. [Activity] Recommendations with RBM's, part 2.srt	15.9 KB
5. [Activity] Evaluating the RBM Recommender.mp4	39.5 MB
5. [Activity] Evaluating the RBM Recommender.srt	7.5 KB
6. [Exercise] Tuning Restricted Boltzmann Machines.mp4	35.2 MB
6. [Exercise] Tuning Restricted Boltzmann Machines.srt	4.3 KB
7. Exercise Results Tuning a RBM Recommender.mp4	12.4 MB
7. Exercise Results Tuning a RBM Recommender.srt	2.7 KB
8. Auto-Encoders for Recommendations Deep Learning for Recs.mp4	28.2 MB
8. Auto-Encoders for Recommendations Deep Learning for Recs.srt	10.6 KB
9. [Activity] Recommendations with Deep Neural Networks.mp4	79.1 MB
9. [Activity] Recommendations with Deep Neural Networks.srt	15.0 KB
10. Clickstream Recommendations with RNN's.mp4	51.1 MB
10. Clickstream Recommendations with RNN's.srt	17.2 KB
11. [Exercise] Get GRU4Rec Working on your Desktop.mp4	7.8 MB
11. [Exercise] Get GRU4Rec Working on your Desktop.srt	6.0 KB
12. Exercise Results GRU4Rec in Action.mp4	65.7 MB
12. Exercise Results GRU4Rec in Action.srt	18.6 KB
13. Bleeding Edge Alert! Deep Factorization Machines.mp4	60.1 MB
13. Bleeding Edge Alert! Deep Factorization Machines.srt	12.9 KB
14. More Emerging Tech to Watch.mp4	29.0 MB
14. More Emerging Tech to Watch.srt	11.9 KB
/.../10. Scaling it Up/
1. [Activity] Introduction and Installation of Apache Spark.mp4	55.9 MB
1. [Activity] Introduction and Installation of Apache Spark.srt	9.5 KB
2. Apache Spark Architecture.mp4	18.2 MB
2. Apache Spark Architecture.srt	11.6 KB
3. [Activity] Movie Recommendations with Spark, Matrix Factorization, and ALS.mp4	58.3 MB
3. [Activity] Movie Recommendations with Spark, Matrix Factorization, and ALS.srt	12.6 KB
4. [Activity] Recommendations from 20 million ratings with Spark.mp4	53.1 MB
4. [Activity] Recommendations from 20 million ratings with Spark.srt	9.4 KB
5. Amazon DSSTNE.mp4	44.4 MB
5. Amazon DSSTNE.srt	10.4 KB
6. DSSTNE in Action.mp4	119.2 MB
6. DSSTNE in Action.srt	13.2 KB
7. Scaling Up DSSTNE.mp4	10.9 MB
7. Scaling Up DSSTNE.srt	4.7 KB
8. AWS SageMaker and Factorization Machines.mp4	16.3 MB
8. AWS SageMaker and Factorization Machines.srt	9.5 KB
9. SageMaker in Action Factorization Machines on one million ratings, in the cloud.mp4	71.7 MB
9. SageMaker in Action Factorization Machines on one million ratings, in the cloud.srt	14.6 KB
/.../11. Real-World Challenges of Recommender Systems/
1. The Cold Start Problem (and solutions).mp4	29.1 MB
1. The Cold Start Problem (and solutions).srt	14.9 KB
2. [Exercise] Implement Random Exploration.mp4	2.3 MB
2. [Exercise] Implement Random Exploration.srt	2.0 KB
3. Exercise Solution Random Exploration.mp4	25.3 MB
3. Exercise Solution Random Exploration.srt	4.7 KB
4. Stoplists.mp4	20.9 MB
4. Stoplists.srt	11.6 KB
5. [Exercise] Implement a Stoplist.mp4	1.4 MB
5. [Exercise] Implement a Stoplist.srt	1.4 KB
6. Exercise Solution Implement a Stoplist.mp4	28.0 MB
6. Exercise Solution Implement a Stoplist.srt	4.8 KB
7. Filter Bubbles, Trust, and Outliers.mp4	96.9 MB
7. Filter Bubbles, Trust, and Outliers.srt	13.7 KB
8. [Exercise] Identify and Eliminate Outlier Users.mp4	1.9 MB
8. [Exercise] Identify and Eliminate Outlier Users.srt	2.0 KB
9. Exercise Solution Outlier Removal.mp4	40.4 MB
9. Exercise Solution Outlier Removal.srt	8.5 KB
10. Fraud, The Perils of Clickstream, and International Concerns.mp4	61.1 MB
10. Fraud, The Perils of Clickstream, and International Concerns.srt	10.9 KB
11. Temporal Effects, and Value-Aware Recommendations.mp4	56.7 MB
11. Temporal Effects, and Value-Aware Recommendations.srt	8.4 KB
/.../12. Case Studies/
1. Case Study YouTube, Part 1.mp4	28.2 MB
1. Case Study YouTube, Part 1.srt	8.1 KB
2. Case Study YouTube, Part 2.mp4	27.5 MB
2. Case Study YouTube, Part 2.srt	16.0 KB
3. Case Study Netflix, Part 1.mp4	28.9 MB
3. Case Study Netflix, Part 1.srt	8.6 KB
4. Case Study Netflix, Part 2.mp4	27.9 MB
4. Case Study Netflix, Part 2.srt	8.6 KB
/.../13. Hybrid Approaches/
1. Hybrid Recommenders and Exercise.mp4	19.3 MB
1. Hybrid Recommenders and Exercise.srt	6.2 KB
2. Exercise Solution Hybrid Recommenders.mp4	34.8 MB
2. Exercise Solution Hybrid Recommenders.srt	9.4 KB
/.../14. Wrapping Up/
1. More to Explore.mp4	40.8 MB
1. More to Explore.srt	5.6 KB
2. Bonus Lecture Discounts to continue your journey!.html	7.3 KB
Total files 223