Recommendation Systems with TensorFlow on GCP
Focused View
Google Cloud
6:46:05
14 View
01 - Introduction.mp4
09:04
02 - Getting started with GCP and Qwiklabs.mp4
03:48
03 - Introduction.mp4
05:33
04 - Types of Recommendation Systems.mp4
02:43
05 - Content-Based or Collaborative.mp4
06:19
06 - Recommendation System Pitfalls.mp4
03:41
07 - Discussion.mp4
01:34
08 - Content-Based Recommendation Systems.mp4
01:52
09 - Similarity Measures.mp4
03:16
10 - Building a User Vector.mp4
03:42
11 - Making Recommendations Using a User Vector.mp4
01:44
12 - Making Recommendations for Many Users.mp4
06:50
13 - Lab intro - Create a Content-Based Recommendation System.mp4
00:20
14 - Content-Based Filtering by Hand.mp4
00:10
15 - Lab Solution -Create a Content-Based Recommendation System.mp4
13:57
16 - Using Neural Networks for Content-Based Recommendation Systems.mp4
04:07
17 - Lab Intro - Create a Content-Based Recommendation System Using a Neural Network.mp4
00:35
18 - Content-Based Filtering using Neural Networks.mp4
00:10
19 - Lab Solution -Create a Content-Based Recommendation System Using a Neural Network.mp4
36:36
20 - Types of User Feedback Data.mp4
07:26
21 - Embedding Users and Items.mp4
12:46
22 - Factorization Approaches.mp4
06:42
23 - The ALS Algorithm.mp4
05:21
24 - Preparing Input Data for ALS.mp4
06:03
25 - Creating Sparse Tensors For Efficient WALS Input.mp4
03:24
26 - Instantiating a WALS Estimator -From Input to Estimator.mp4
05:11
27 - Instantiating a WAL Estimator -Decoding TFRecords.mp4
03:50
28 - Instantiating a WALS Estimator -Recovering Keys.mp4
12:32
29 - Instantiating a WALS Estimator -Training and Prediction.mp4
05:43
30 - Lab Intro -Collaborative Filtering with Google Analytics Data.mp4
00:48
31 - Collaborative Filtering on Google Analytics data.mp4
00:10
32 - Lab Solution -Collaborative Filtering with Google Analytics Data.mp4
44:01
33 - Issues with Collaborative Filtering.mp4
04:14
34 - Productionized WALS Demo.mp4
21:44
35 - Cold Starts.mp4
05:33
36 - Hybrid Recommendation Systems.mp4
14:47
37 - Lab -Designing a Hybrid Recommendation System.mp4
06:14
38 - Lab -Designing a Hybrid Collaborative Filtering Recommendation System.mp4
03:56
39 - Lab -Designing a Hybrid Knowledge-based Recommendation System.mp4
05:26
40 - Lab Intro - Building a Neural Network Hybrid Recommendation System.mp4
00:27
41 - Neural network hybrid recommendation system on Google Analytics.mp4
00:10
42 - Lab Solution -Building a Neural Network Hybrid Recommendation System.mp4
34:37
43 - Context-Aware Recommendation Systems.mp4
07:47
44 - Context-Aware Algorithms.mp4
05:28
45 - Contextual Postfiltering.mp4
02:30
46 - Modeling Using Context-Aware Algorithms.mp4
05:24
47 - YouTube Recommendation System Case Study -Overview.mp4
03:00
48 - YouTube Recommendation System Case Study -Candidate Generation.mp4
03:21
49 - YouTube Recommendation System Case Study -Ranking.mp4
02:44
50 - Summary.mp4
01:33
51 - Introduction.mp4
04:07
52 - Architecture Overview.mp4
03:08
53 - Cloud Composer Overview.mp4
16:07
54 - Cloud Composer -DAGs.mp4
04:38
55 - Cloud Composer -Operators for ML.mp4
09:04
56 - Cloud Composer -Scheduling.mp4
01:47
57 - Cloud Composer -Triggering Workflows with Cloud Functions.mp4
03:51
58 - Cloud Composer -Monitoring and Logging.mp4
05:09
59 - Lab Intro - End-to-End Recommendation System.mp4
01:14
60 - End to End Recommendation System.mp4
00:10
61 - Course Summary 1.mp4
02:43
62 - Course Summary 2.mp4
05:14
Description
In this course, you'll apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine.
What You'll Learn?
In this course, you'll apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine.
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Google Cloud
Instructor's CoursesGoogle Cloud can help solve your toughest problems and grow your business. With Google Cloud, their infrastructure is your infrastructure. Their tools are your tools. And their innovations are your innovations.
Pluralsight
View courses PluralsightPluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.
- language english
- Training sessions 62
- duration 6:46:05
- level advanced
- Release Date 2023/10/15
