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[DesireCourse.Com] Udemy - Deployment of Machine Learning Models
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[DesireCourse.Com] Udemy - Deployment of Machine Learning Models
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文件列表
4. Building a Reproducible Machine Learning Pipeline/3. Designing a Custom Pipeline.mp4
160.3 MB
2. Machine Learning Pipeline - Research Environment/6. Data Analysis - Demo.mp4
142.0 MB
2. Machine Learning Pipeline - Research Environment/7. Feature Engineering - Demo.mp4
102.9 MB
13. A Deep Learning Model with Big Data/3. Building a CNN in the Research Environment.mp4
93.1 MB
4. Building a Reproducible Machine Learning Pipeline/2. Procedural Programming Pipeline.mp4
90.4 MB
4. Building a Reproducible Machine Learning Pipeline/5. Third Party Pipeline Create Scikit-Learn compatible Feature Transformers.mp4
88.4 MB
13. A Deep Learning Model with Big Data/4. Production Code for a CNN Learning Pipeline.mp4
83.4 MB
5. Course Setup and Key Tools/9. Section5.5b - Virtualenv Introduction.mp4
83.2 MB
7. Serving the model via REST API/7. 7.6 - API Schema Validation.mp4
81.9 MB
3. Machine Learning System Architecture/5. Building a Reproducible Machine Learning Pipeline.mp4
80.8 MB
6. Creating a Machine Learning Pipeline Application/9. 6.8 - Building the Package.mp4
79.6 MB
13. A Deep Learning Model with Big Data/8. 13.8 - Packaging the CNN.mp4
75.4 MB
6. Creating a Machine Learning Pipeline Application/8. 6.7 - Versioning and Logging.mp4
73.9 MB
8. Continuous Integration and Deployment Pipelines/4. 8.4 - Publishing the Model to Gemfury.mp4
72.5 MB
2. Machine Learning Pipeline - Research Environment/10. Getting Ready for Deployment - Demo.mp4
71.1 MB
2. Machine Learning Pipeline - Research Environment/1. Machine Learning Pipeline Overview.mp4
63.5 MB
12. Deploying to IaaS (AWS ECS)/12. 12.11 - Creating the ECS Cluster with the EC2 Launch Method.mp4
62.8 MB
2. Machine Learning Pipeline - Research Environment/2. Machine Learning Pipeline Feature Engineering.mp4
60.5 MB
4. Building a Reproducible Machine Learning Pipeline/4. Leveraging a Third Party Pipeline Scikit-Learn.mp4
59.4 MB
8. Continuous Integration and Deployment Pipelines/3. 8.3 - Setup Circle CI Config.mp4
53.3 MB
9. Differential Testing/2. 9.2 - Setting up Differential Tests.mp4
52.7 MB
8. Continuous Integration and Deployment Pipelines/5. 8.5 - Testing the CI Pipeline.mp4
52.6 MB
12. Deploying to IaaS (AWS ECS)/10. 12.9 - Uploading Images to the Elastic Container Registry (ECR).mp4
52.2 MB
2. Machine Learning Pipeline - Research Environment/3. Machine Learning Pipeline Feature Selection.mp4
50.8 MB
1. Introduction/2. Course curriculum overview.mp4
50.6 MB
11. Running Apps with Containers (Docker)/5. 11.5 Releasing to Heroku with Docker.mp4
49.2 MB
6. Creating a Machine Learning Pipeline Application/2. 6.2 - Training the Model.mp4
48.5 MB
6. Creating a Machine Learning Pipeline Application/3. 6.3 - Connecting the Pipeline.mp4
47.6 MB
6. Creating a Machine Learning Pipeline Application/5. 6.4 - Making Predictions with the Model.mp4
46.9 MB
8. Continuous Integration and Deployment Pipelines/1.1 section8.1.mp4.mp4
43.9 MB
13. A Deep Learning Model with Big Data/9. 13.9 - Adding the CNN to the API.mp4
43.3 MB
3. Machine Learning System Architecture/2. Specific Challenges of Machine Learning Systems.mp4
41.0 MB
7. Serving the model via REST API/5. 7.4 - Adding the Prediction Endpoint.mp4
40.8 MB
12. Deploying to IaaS (AWS ECS)/11. 12.10 - Creating the ECS Cluster with Fargate Launch Method.mp4
40.0 MB
5. Course Setup and Key Tools/3. Section 5.3 - How to Use the Course Resources, Monorepos + Git Refresher.mp4
39.6 MB
1. Introduction/1. Introduction to the course.mp4
39.4 MB
5. Course Setup and Key Tools/4. Section5.3b - Opening Pull Requests.mp4
37.9 MB
2. Machine Learning Pipeline - Research Environment/8. Feature Selection - Demo.mp4
37.1 MB
7. Serving the model via REST API/2. 7.2 - Creating the API Skeleton.mp4
37.1 MB
2. Machine Learning Pipeline - Research Environment/9. Model Building - Demo.mp4
35.8 MB
9. Differential Testing/3. 9.3 - Differential Tests in CI (Part 1 of 2).mp4
35.2 MB
7. Serving the model via REST API/4. 7.3 - Adding Config and Logging.mp4
34.6 MB
9. Differential Testing/4. 9.4 - Differential Tests in CI (Part 2 of 2).mp4
34.4 MB
6. Creating a Machine Learning Pipeline Application/6. 6.5 - Data Validation in the Model Package.mp4
34.1 MB
10. Deploying to a PaaS (Heroku) without Containers/3. 10.3 - Heroku Config.mp4
33.8 MB
11. Running Apps with Containers (Docker)/1. 11.1 Introduction to Containers and Docker.mp4
33.0 MB
5. Course Setup and Key Tools/13. Section 5.7 - Engineering and Python Best Practices.mp4
32.9 MB
12. Deploying to IaaS (AWS ECS)/13. 12.12 - Updating the Cluster Containers.mp4
32.5 MB
3. Machine Learning System Architecture/3. Machine Learning System Approaches.mp4
31.5 MB
3. Machine Learning System Architecture/4. Machine Learning System Component Breakdown.mp4
30.9 MB
10. Deploying to a PaaS (Heroku) without Containers/5. 10.5 - Deploying to Heroku via CI.mp4
30.5 MB
12. Deploying to IaaS (AWS ECS)/7. 12.6 - Installing the AWS CLI.mp4
30.3 MB
4. Building a Reproducible Machine Learning Pipeline/8. Bonus Should feature selection be part of the pipeline.mp4
30.2 MB
8. Continuous Integration and Deployment Pipelines/1. 8.1 - Introduction to CICD.mp4
29.8 MB
5. Course Setup and Key Tools/2. Section 5.2 - Installing and Configuring Git.mp4
29.2 MB
10. Deploying to a PaaS (Heroku) without Containers/1. 10.1 - Introduction.mp4
28.2 MB
11. Running Apps with Containers (Docker)/4. 11.4 Building and Running the Docker Container.mp4
28.0 MB
11. Running Apps with Containers (Docker)/2. 11.2 Installing Docker.mp4
27.9 MB
6. Creating a Machine Learning Pipeline Application/7. 6.6 - Feature Engineering in the Pipeline.mp4
27.5 MB
12. Deploying to IaaS (AWS ECS)/2. 12.2 - AWS Costs and Caution.mp4
26.7 MB
2. Machine Learning Pipeline - Research Environment/11. Bonus Machine Learning Pipeline Additional Resources.mp4
26.7 MB
5. Course Setup and Key Tools/11. Section5.5d - Virtualenv refresher.mp4
26.6 MB
7. Serving the model via REST API/1. 7.1 - Introduction.mp4
26.3 MB
12. Deploying to IaaS (AWS ECS)/4. 12.3b - Container Orchestration Options Kubernetes, ECS, Docker Swarm.mp4
24.9 MB
12. Deploying to IaaS (AWS ECS)/15. 12.14 - Deploying to ECS via the CI pipeline.mp4
24.7 MB
12. Deploying to IaaS (AWS ECS)/6. 12.5 - Setting Permissions with IAM.mp4
24.3 MB
12. Deploying to IaaS (AWS ECS)/3. 12.3a - Intro to AWS ECS.mp4
23.9 MB
5. Course Setup and Key Tools/7. Section 5.4b - System Path and Pythonpath Demo.mp4
22.9 MB
11. Running Apps with Containers (Docker)/3. 11.3 Creating Our API App Dockerfile.mp4
22.6 MB
10. Deploying to a PaaS (Heroku) without Containers/2. 10.2 - Heroku Account Creation.mp4
21.9 MB
12. Deploying to IaaS (AWS ECS)/8. 12.7 - Configuring the AWS CLI.mp4
21.8 MB
13. A Deep Learning Model with Big Data/10. 13.10 - Additional Considerations and Wrap Up.mp4
21.8 MB
4. Building a Reproducible Machine Learning Pipeline/1. Production Code overview.mp4
20.2 MB
12. Deploying to IaaS (AWS ECS)/1. 12.1 - Introduction to AWS.mp4
19.6 MB
9. Differential Testing/1. 9.1 - Introduction.mp4
19.5 MB
5. Course Setup and Key Tools/5. Section5.3c - Primer on Monorepos.mp4
19.2 MB
2. Machine Learning Pipeline - Research Environment/4. Machine Learning Pipeline Model Building.mp4
18.7 MB
7. Serving the model via REST API/3. 7.2b - Flask Crash Course.mp4
18.7 MB
1. Introduction/3. Knowledge requirements.mp4
18.0 MB
13. A Deep Learning Model with Big Data/5. Reproducibility in Neural Networks.mp4
17.8 MB
13. A Deep Learning Model with Big Data/2. Introduction to a Large Dataset - Plant Seedlings Images.mp4
17.5 MB
5. Course Setup and Key Tools/1. Section 5.1 - Introduction.mp4
16.7 MB
7. Serving the model via REST API/6. 7.5 - Adding a Version Endpoint.mp4
16.2 MB
13. A Deep Learning Model with Big Data/1. Challenges of using Big Data in Machine Learning.mp4
16.0 MB
6. Creating a Machine Learning Pipeline Application/1. 6.1 - Introduction.mp4
15.0 MB
10. Deploying to a PaaS (Heroku) without Containers/6. 10.6 - Wrap Up.mp4
14.2 MB
1. Introduction/6.1 DMLM_Slides.zip.zip
14.0 MB
6. Creating a Machine Learning Pipeline Application/10. 6.9 - Wrap Up.mp4
13.9 MB
9. Differential Testing/5. 9.5 Wrap Up.mp4
13.3 MB
5. Course Setup and Key Tools/12. Section 5.6 - Text Editors IDEs.mp4
13.0 MB
10. Deploying to a PaaS (Heroku) without Containers/4. 10.4 - Testing the Deployment Manually.mp4
12.9 MB
3. Machine Learning System Architecture/1. Machine Learning System Architecture and Why it Matters.mp4
11.4 MB
8. Continuous Integration and Deployment Pipelines/2. 8.2 - Setting up CircleCI.mp4
11.1 MB
4. Building a Reproducible Machine Learning Pipeline/6. Third Party Pipeline Closing Remarks.mp4
10.5 MB
5. Course Setup and Key Tools/10. Section5.5c - Requirements files Introduction.mp4
10.0 MB
12. Deploying to IaaS (AWS ECS)/9. 12.8 - Intro the Elastic Container Registry (ECR).mp4
9.8 MB
12. Deploying to IaaS (AWS ECS)/16. 12.15 - Wrap Up.mp4
9.4 MB
5. Course Setup and Key Tools/6. Section 5.4a - Operating System Differences and Gotchas.mp4
8.6 MB
5. Course Setup and Key Tools/8. Section 5.5a - Quick Word for More Advanced Students.mp4
8.6 MB
11. Running Apps with Containers (Docker)/6. 11.6 - Wrap Up.mp4
8.1 MB
12. Deploying to IaaS (AWS ECS)/14. 12.13 - Tearing down the ECS Cluster.mp4
7.3 MB
7. Serving the model via REST API/8. 7.7 - Wrap Up.mp4
6.6 MB
5. Course Setup and Key Tools/14. Section 5.8 - Wrap Up.mp4
6.3 MB
8. Continuous Integration and Deployment Pipelines/6. 8.6 - Wrap Up.mp4
5.6 MB
12. Deploying to IaaS (AWS ECS)/5. 12.4 - Create an AWS Account.mp4
5.1 MB
1. Introduction/7.1 DMLM_Notes.zip.zip
1.6 MB
13. A Deep Learning Model with Big Data/3.1 CNN_Analysis_and Model.zip.zip
1.6 MB
2. Machine Learning Pipeline - Research Environment/5.1 MLPipeline-Notebooks.zip.zip
1.2 MB
14. Common Issues found during deployment/1.1 Troubleshooting.pdf.pdf
228.7 kB
7. Serving the model via REST API/2.1 Section7.2_Notes.pdf.pdf
149.8 kB
8. Continuous Integration and Deployment Pipelines/4.1 Section8.4_Notes.pdf.pdf
103.2 kB
9. Differential Testing/4.1 Section9.4_Notes.pdf.pdf
103.0 kB
5. Course Setup and Key Tools/4.1 Section5.3b_Notes.pdf.pdf
102.0 kB
6. Creating a Machine Learning Pipeline Application/4.1 Section6.4_Notes.pdf.pdf
101.1 kB
6. Creating a Machine Learning Pipeline Application/5.1 Section6.4_Notes.pdf.pdf
101.1 kB
5. Course Setup and Key Tools/2.1 Section5.2_Notes.pdf.pdf
98.8 kB
11. Running Apps with Containers (Docker)/4.1 Section11.4_Notes.pdf.pdf
96.3 kB
5. Course Setup and Key Tools/9.1 Section5.5b_Notes.pdf.pdf
94.4 kB
5. Course Setup and Key Tools/13.1 Section5.7_Notes.pdf.pdf
91.0 kB
8. Continuous Integration and Deployment Pipelines/5.1 Section8.5_Notes.pdf.pdf
91.0 kB
6. Creating a Machine Learning Pipeline Application/9.1 Section6.8_Notes.pdf.pdf
88.0 kB
5. Course Setup and Key Tools/3.1 Section5.3a_Notes.pdf.pdf
87.6 kB
5. Course Setup and Key Tools/12.1 Section5.6_Notes.pdf.pdf
86.9 kB
7. Serving the model via REST API/6.1 Section7.5_Notes.pdf.pdf
86.3 kB
5. Course Setup and Key Tools/11.1 Section5.5_Notes.pdf.pdf
85.8 kB
7. Serving the model via REST API/7.1 Section7.6_Notes.pdf.pdf
85.7 kB
7. Serving the model via REST API/4.1 Section7.3_Notes.pdf.pdf
85.1 kB
12. Deploying to IaaS (AWS ECS)/8.1 Section12.7_Notes.pdf.pdf
85.0 kB
11. Running Apps with Containers (Docker)/6.1 Section11.6_Notes.pdf.pdf
84.4 kB
7. Serving the model via REST API/3.1 Section7.2b_Notes.pdf.pdf
83.5 kB
7. Serving the model via REST API/5.1 Section7.4_Notes.pdf.pdf
83.5 kB
6. Creating a Machine Learning Pipeline Application/8.1 Section6.7_Notes.pdf.pdf
83.2 kB
6. Creating a Machine Learning Pipeline Application/6.1 Section6.5_Notes.pdf.pdf
81.2 kB
6. Creating a Machine Learning Pipeline Application/7.1 Section6.6_Notes.pdf.pdf
80.8 kB
3. Machine Learning System Architecture/4.1 Section3.4_Notes.pdf.pdf
80.7 kB
11. Running Apps with Containers (Docker)/2.1 Section11.2_Notes.pdf.pdf
79.7 kB
10. Deploying to a PaaS (Heroku) without Containers/1.1 Section10.1_Notes.pdf.pdf
78.5 kB
6. Creating a Machine Learning Pipeline Application/3.1 Section6.3_Notes.pdf.pdf
77.2 kB
12. Deploying to IaaS (AWS ECS)/2.1 Section12.2_Notes.pdf.pdf
76.5 kB
5. Course Setup and Key Tools/10.1 Section5.5c_Notes.pdf.pdf
75.5 kB
12. Deploying to IaaS (AWS ECS)/10.1 Section12.9_Notes.pdf.pdf
74.1 kB
13. A Deep Learning Model with Big Data/8.1 Section13.8_Notes.pdf.pdf
73.3 kB
3. Machine Learning System Architecture/3.1 Section3.3_Notes.pdf.pdf
72.7 kB
11. Running Apps with Containers (Docker)/1.1 Section11.1_Notes.pdf.pdf
71.9 kB
10. Deploying to a PaaS (Heroku) without Containers/4.1 Section10.4_Notes.pdf.pdf
71.4 kB
9. Differential Testing/5.1 Section9.5_Notes.pdf.pdf
71.1 kB
10. Deploying to a PaaS (Heroku) without Containers/3.1 Section10.3_Notes.pdf.pdf
70.6 kB
10. Deploying to a PaaS (Heroku) without Containers/5.1 Section10.5_Notes.pdf.pdf
69.5 kB
12. Deploying to IaaS (AWS ECS)/13.1 Section12.12_Notes.pdf.pdf
69.1 kB
9. Differential Testing/2.1 Section9.2_Notes.pdf.pdf
66.5 kB
5. Course Setup and Key Tools/6.1 Section5.4_Notes.pdf.pdf
66.0 kB
5. Course Setup and Key Tools/7.1 Section5.4_Notes.pdf.pdf
66.0 kB
12. Deploying to IaaS (AWS ECS)/15.1 Section12.14_Notes.pdf.pdf
65.7 kB
10. Deploying to a PaaS (Heroku) without Containers/6.1 Section10.6_Notes.pdf.pdf
65.4 kB
8. Continuous Integration and Deployment Pipelines/3.1 Section8.3_Notes.pdf.pdf
65.4 kB
7. Serving the model via REST API/1.1 Section7.1_Notes.pdf.pdf
64.9 kB
10. Deploying to a PaaS (Heroku) without Containers/2.1 Section10.2_Notes.pdf.pdf
62.9 kB
12. Deploying to IaaS (AWS ECS)/14.1 Section12.13_Notes.pdf.pdf
61.5 kB
13. A Deep Learning Model with Big Data/10.1 Section13.10_Notes.pdf.pdf
61.5 kB
8. Continuous Integration and Deployment Pipelines/2.1 Section8.2_Notes.pdf.pdf
60.2 kB
11. Running Apps with Containers (Docker)/3.1 Section11.3_Notes.pdf.pdf
59.9 kB
12. Deploying to IaaS (AWS ECS)/6.1 Section12.5_Notes.pdf.pdf
59.3 kB
12. Deploying to IaaS (AWS ECS)/12.1 Section12.11_Notes.pdf.pdf
58.8 kB
12. Deploying to IaaS (AWS ECS)/7.1 Section12.6_Notes.pdf.pdf
58.3 kB
12. Deploying to IaaS (AWS ECS)/11.1 Section12.10_Notes.pdf.pdf
58.2 kB
12. Deploying to IaaS (AWS ECS)/16.1 Section12.15_Notes.pdf.pdf
57.9 kB
11. Running Apps with Containers (Docker)/5.1 Section11.5_Notes.pdf.pdf
57.9 kB
12. Deploying to IaaS (AWS ECS)/9.1 Section12.8_Notes.pdf.pdf
56.6 kB
12. Deploying to IaaS (AWS ECS)/3.1 Section12.3_Notes.pdf.pdf
56.5 kB
12. Deploying to IaaS (AWS ECS)/4.1 Section12.3_Notes.pdf.pdf
56.5 kB
5. Course Setup and Key Tools/5.1 Section5.3c_Notes.pdf.pdf
55.2 kB
12. Deploying to IaaS (AWS ECS)/5.1 Section12.4_Notes.pdf.pdf
54.8 kB
13. A Deep Learning Model with Big Data/9.1 Section13.9_Notes.pdf.pdf
54.5 kB
2. Machine Learning Pipeline - Research Environment/6. Data Analysis - Demo.vtt
21.8 kB
4. Building a Reproducible Machine Learning Pipeline/3. Designing a Custom Pipeline.vtt
20.3 kB
2. Machine Learning Pipeline - Research Environment/7. Feature Engineering - Demo.vtt
14.4 kB
4. Building a Reproducible Machine Learning Pipeline/5. Third Party Pipeline Create Scikit-Learn compatible Feature Transformers.vtt
14.1 kB
4. Building a Reproducible Machine Learning Pipeline/2. Procedural Programming Pipeline.vtt
13.0 kB
3. Machine Learning System Architecture/5. Building a Reproducible Machine Learning Pipeline.vtt
13.0 kB
2. Machine Learning Pipeline - Research Environment/3. Machine Learning Pipeline Feature Selection.vtt
11.5 kB
13. A Deep Learning Model with Big Data/3. Building a CNN in the Research Environment.vtt
10.5 kB
4. Building a Reproducible Machine Learning Pipeline/4. Leveraging a Third Party Pipeline Scikit-Learn.vtt
9.8 kB
2. Machine Learning Pipeline - Research Environment/2. Machine Learning Pipeline Feature Engineering.vtt
9.5 kB
1. Introduction/2. Course curriculum overview.vtt
9.5 kB
13. A Deep Learning Model with Big Data/4. Production Code for a CNN Learning Pipeline.vtt
9.4 kB
2. Machine Learning Pipeline - Research Environment/10. Getting Ready for Deployment - Demo.vtt
9.2 kB
2. Machine Learning Pipeline - Research Environment/1. Machine Learning Pipeline Overview.vtt
9.0 kB
1. Introduction/1. Introduction to the course.vtt
7.8 kB
6. Creating a Machine Learning Pipeline Application/9. 6.8 - Building the Package.vtt
7.4 kB
8. Continuous Integration and Deployment Pipelines/4. 8.4 - Publishing the Model to Gemfury.vtt
7.4 kB
7. Serving the model via REST API/7. 7.6 - API Schema Validation.vtt
7.3 kB
6. Creating a Machine Learning Pipeline Application/8. 6.7 - Versioning and Logging.vtt
7.2 kB
5. Course Setup and Key Tools/9. Section5.5b - Virtualenv Introduction.vtt
7.1 kB
4. Building a Reproducible Machine Learning Pipeline/8. Bonus Should feature selection be part of the pipeline.vtt
7.0 kB
3. Machine Learning System Architecture/2. Specific Challenges of Machine Learning Systems.vtt
6.9 kB
12. Deploying to IaaS (AWS ECS)/12. 12.11 - Creating the ECS Cluster with the EC2 Launch Method.vtt
6.5 kB
8. Continuous Integration and Deployment Pipelines/3. 8.3 - Setup Circle CI Config.vtt
6.4 kB
13. A Deep Learning Model with Big Data/8. 13.8 - Packaging the CNN.vtt
6.3 kB
3. Machine Learning System Architecture/4. Machine Learning System Component Breakdown.vtt
6.2 kB
5. Course Setup and Key Tools/13. Section 5.7 - Engineering and Python Best Practices.vtt
6.1 kB
4. Building a Reproducible Machine Learning Pipeline/5.1 preprocessors.py.py
5.5 kB
6. Creating a Machine Learning Pipeline Application/2. 6.2 - Training the Model.vtt
5.4 kB
11. Running Apps with Containers (Docker)/5. 11.5 Releasing to Heroku with Docker.vtt
5.3 kB
3. Machine Learning System Architecture/3. Machine Learning System Approaches.vtt
5.3 kB
2. Machine Learning Pipeline - Research Environment/9. Model Building - Demo.vtt
5.3 kB
8. Continuous Integration and Deployment Pipelines/1. 8.1 - Introduction to CICD.vtt
5.1 kB
8. Continuous Integration and Deployment Pipelines/5. 8.5 - Testing the CI Pipeline.vtt
5.0 kB
10. Deploying to a PaaS (Heroku) without Containers/3. 10.3 - Heroku Config.vtt
5.0 kB
6. Creating a Machine Learning Pipeline Application/5. 6.4 - Making Predictions with the Model.vtt
4.9 kB
13. A Deep Learning Model with Big Data/4.1 CNNProdCode.zip.zip
4.8 kB
12. Deploying to IaaS (AWS ECS)/3. 12.3a - Intro to AWS ECS.vtt
4.6 kB
10. Deploying to a PaaS (Heroku) without Containers/1. 10.1 - Introduction.vtt
4.5 kB
1. Introduction/3. Knowledge requirements.vtt
4.5 kB
11. Running Apps with Containers (Docker)/1. 11.1 Introduction to Containers and Docker.vtt
4.5 kB
12. Deploying to IaaS (AWS ECS)/10. 12.9 - Uploading Images to the Elastic Container Registry (ECR).vtt
4.3 kB
9. Differential Testing/2. 9.2 - Setting up Differential Tests.vtt
4.3 kB
2. Machine Learning Pipeline - Research Environment/8. Feature Selection - Demo.vtt
4.2 kB
6. Creating a Machine Learning Pipeline Application/3. 6.3 - Connecting the Pipeline.vtt
4.1 kB
7. Serving the model via REST API/5. 7.4 - Adding the Prediction Endpoint.vtt
4.1 kB
13. A Deep Learning Model with Big Data/9. 13.9 - Adding the CNN to the API.vtt
4.0 kB
1. Introduction/5. Guide to Setting up your Computer.html
4.0 kB
7. Serving the model via REST API/4. 7.3 - Adding Config and Logging.vtt
4.0 kB
12. Deploying to IaaS (AWS ECS)/11. 12.10 - Creating the ECS Cluster with Fargate Launch Method.vtt
3.9 kB
13. A Deep Learning Model with Big Data/5. Reproducibility in Neural Networks.vtt
3.8 kB
7. Serving the model via REST API/1. 7.1 - Introduction.vtt
3.8 kB
10. Deploying to a PaaS (Heroku) without Containers/5. 10.5 - Deploying to Heroku via CI.vtt
3.8 kB
11. Running Apps with Containers (Docker)/4. 11.4 Building and Running the Docker Container.vtt
3.7 kB
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