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[FTUForum.com] [UDEMY] Deployment of Machine Learning Models [FTU]
magnet:?xt=urn:btih:3b823b10b12df325cf7a086be6f52a79802fd8c0&dn=[FTUForum.com] [UDEMY] Deployment of Machine Learning Models [FTU]
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3b823b10b12df325cf7a086be6f52a79802fd8c0
infohash:
104
文件数量
3.63 GB
文件大小
2020-12-20 01:54
创建日期
2024-12-26 15:44
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FTUForum
com
UDEMY
Deployment
of
Machine
Learning
Models
FTU
10. Deploying to a PaaS (Heroku) without Containers/1. 10.1 - Introduction.mp4 26.9 MB
10. Deploying to a PaaS (Heroku) without Containers/2. 10.2 - Heroku Account Creation.mp4 20.91 MB
10. Deploying to a PaaS (Heroku) without Containers/3. 10.3 - Heroku Config.mp4 32.22 MB
10. Deploying to a PaaS (Heroku) without Containers/4. 10.4 - Testing the Deployment Manually.mp4 12.35 MB
10. Deploying to a PaaS (Heroku) without Containers/5. 10.5 - Deploying to Heroku via CI.mp4 29.07 MB
10. Deploying to a PaaS (Heroku) without Containers/6. 10.6 - Wrap Up.mp4 13.51 MB
11. Running Apps with Containers (Docker)/1. 11.1 Introduction to Containers and Docker.mp4 31.51 MB
11. Running Apps with Containers (Docker)/2. 11.2 Installing Docker.mp4 26.65 MB
11. Running Apps with Containers (Docker)/3. 11.3 Creating Our API App Dockerfile.mp4 21.6 MB
11. Running Apps with Containers (Docker)/4. 11.4 Building and Running the Docker Container.mp4 26.73 MB
11. Running Apps with Containers (Docker)/5. 11.5 Releasing to Heroku with Docker.mp4 46.93 MB
11. Running Apps with Containers (Docker)/6. 11.6 - Wrap Up.mp4 7.73 MB
12. Deploying to IaaS (AWS ECS)/10. 12.9 - Uploading Images to the Elastic Container Registry (ECR).mp4 49.77 MB
12. Deploying to IaaS (AWS ECS)/11. 12.10 - Creating the ECS Cluster with Fargate Launch Method.mp4 38.12 MB
12. Deploying to IaaS (AWS ECS)/1. 12.1 - Introduction to AWS.mp4 18.7 MB
12. Deploying to IaaS (AWS ECS)/12. 12.11 - Creating the ECS Cluster with the EC2 Launch Method.mp4 59.91 MB
12. Deploying to IaaS (AWS ECS)/13. 12.12 - Updating the Cluster Containers.mp4 30.97 MB
12. Deploying to IaaS (AWS ECS)/14. 12.13 - Tearing down the ECS Cluster.mp4 6.96 MB
12. Deploying to IaaS (AWS ECS)/15. 12.14 - Deploying to ECS via the CI pipeline.mp4 23.54 MB
12. Deploying to IaaS (AWS ECS)/16. 12.15 - Wrap Up.mp4 8.97 MB
12. Deploying to IaaS (AWS ECS)/2. 12.2 - AWS Costs and Caution.mp4 25.46 MB
12. Deploying to IaaS (AWS ECS)/3. 12.3a - Intro to AWS ECS.mp4 22.79 MB
12. Deploying to IaaS (AWS ECS)/4. 12.3b - Container Orchestration Options Kubernetes, ECS, Docker Swarm.mp4 23.79 MB
12. Deploying to IaaS (AWS ECS)/5. 12.4 - Create an AWS Account.mp4 4.9 MB
12. Deploying to IaaS (AWS ECS)/6. 12.5 - Setting Permissions with IAM.mp4 23.21 MB
12. Deploying to IaaS (AWS ECS)/7. 12.6 - Installing the AWS CLI.mp4 28.93 MB
12. Deploying to IaaS (AWS ECS)/8. 12.7 - Configuring the AWS CLI.mp4 20.84 MB
12. Deploying to IaaS (AWS ECS)/9. 12.8 - Intro the Elastic Container Registry (ECR).mp4 9.37 MB
13. A Deep Learning Model with Big Data/10. 13.10 - Additional Considerations and Wrap Up.mp4 20.76 MB
13. A Deep Learning Model with Big Data/1. Challenges of using Big Data in Machine Learning.mp4 15.3 MB
13. A Deep Learning Model with Big Data/2. Introduction to a Large Dataset - Plant Seedlings Images.mp4 16.65 MB
13. A Deep Learning Model with Big Data/3. Building a CNN in the Research Environment.mp4 88.8 MB
13. A Deep Learning Model with Big Data/4. Production Code for a CNN Learning Pipeline.mp4 79.51 MB
13. A Deep Learning Model with Big Data/5. Reproducibility in Neural Networks.mp4 17.02 MB
13. A Deep Learning Model with Big Data/8. 13.8 - Packaging the CNN.mp4 71.88 MB
13. A Deep Learning Model with Big Data/9. 13.9 - Adding the CNN to the API.mp4 41.32 MB
1. Introduction/1. Introduction to the course.mp4 37.59 MB
1. Introduction/2. Course curriculum overview.mp4 48.21 MB
1. Introduction/3. Knowledge requirements.mp4 17.17 MB
2. Machine Learning Pipeline - Research Environment/10. Getting Ready for Deployment - Demo.mp4 67.84 MB
2. Machine Learning Pipeline - Research Environment/11. Bonus Machine Learning Pipeline Additional Resources.mp4 25.43 MB
2. Machine Learning Pipeline - Research Environment/1. Machine Learning Pipeline Overview.mp4 60.54 MB
2. Machine Learning Pipeline - Research Environment/2. Machine Learning Pipeline Feature Engineering.mp4 57.72 MB
2. Machine Learning Pipeline - Research Environment/3. Machine Learning Pipeline Feature Selection.mp4 48.42 MB
2. Machine Learning Pipeline - Research Environment/4. Machine Learning Pipeline Model Building.mp4 17.81 MB
2. Machine Learning Pipeline - Research Environment/6. Data Analysis - Demo.mp4 135.44 MB
2. Machine Learning Pipeline - Research Environment/7. Feature Engineering - Demo.mp4 98.16 MB
2. Machine Learning Pipeline - Research Environment/8. Feature Selection - Demo.mp4 35.38 MB
2. Machine Learning Pipeline - Research Environment/9. Model Building - Demo.mp4 34.1 MB
3. Machine Learning System Architecture/1. Machine Learning System Architecture and Why it Matters.mp4 10.9 MB
3. Machine Learning System Architecture/2. Specific Challenges of Machine Learning Systems.mp4 39.06 MB
3. Machine Learning System Architecture/3. Machine Learning System Approaches.mp4 30.02 MB
3. Machine Learning System Architecture/4. Machine Learning System Component Breakdown.mp4 29.51 MB
3. Machine Learning System Architecture/5. Building a Reproducible Machine Learning Pipeline.mp4 77.09 MB
4. Building a Reproducible Machine Learning Pipeline/1. Production Code overview.mp4 19.22 MB
4. Building a Reproducible Machine Learning Pipeline/2. Procedural Programming Pipeline.mp4 86.19 MB
4. Building a Reproducible Machine Learning Pipeline/3. Designing a Custom Pipeline.mp4 152.88 MB
4. Building a Reproducible Machine Learning Pipeline/4. Leveraging a Third Party Pipeline Scikit-Learn.mp4 56.67 MB
4. Building a Reproducible Machine Learning Pipeline/5. Third Party Pipeline Create Scikit-Learn compatible Feature Transformers.mp4 84.34 MB
4. Building a Reproducible Machine Learning Pipeline/6. Third Party Pipeline Closing Remarks.mp4 9.97 MB
4. Building a Reproducible Machine Learning Pipeline/8. Bonus Should feature selection be part of the pipeline.mp4 28.84 MB
5. Course Setup and Key Tools/10. Section5.5c - Requirements files Introduction.mp4 9.55 MB
5. Course Setup and Key Tools/11. Section5.5d - Virtualenv refresher.mp4 25.36 MB
5. Course Setup and Key Tools/12. Section 5.6 - Text Editors IDEs.mp4 12.39 MB
5. Course Setup and Key Tools/13. Section 5.7 - Engineering and Python Best Practices.mp4 31.4 MB
5. Course Setup and Key Tools/14. Section 5.8 - Wrap Up.mp4 6.02 MB
5. Course Setup and Key Tools/1. Section 5.1 - Introduction.mp4 15.94 MB
5. Course Setup and Key Tools/2. Section 5.2 - Installing and Configuring Git.mp4 27.83 MB
5. Course Setup and Key Tools/3. Section 5.3 - How to Use the Course Resources, Monorepos + Git Refresher.mp4 37.81 MB
5. Course Setup and Key Tools/4. Section5.3b - Opening Pull Requests.mp4 36.17 MB
5. Course Setup and Key Tools/5. Section5.3c - Primer on Monorepos.mp4 18.35 MB
5. Course Setup and Key Tools/6. Section 5.4a - Operating System Differences and Gotchas.mp4 8.21 MB
5. Course Setup and Key Tools/7. Section 5.4b - System Path and Pythonpath Demo.mp4 21.83 MB
5. Course Setup and Key Tools/8. Section 5.5a - Quick Word for More Advanced Students.mp4 8.2 MB
5. Course Setup and Key Tools/9. Section5.5b - Virtualenv Introduction.mp4 79.34 MB
6. Creating a Machine Learning Pipeline Application/10. 6.9 - Wrap Up.mp4 13.25 MB
6. Creating a Machine Learning Pipeline Application/1. 6.1 - Introduction.mp4 14.28 MB
6. Creating a Machine Learning Pipeline Application/2. 6.2 - Training the Model.mp4 46.22 MB
6. Creating a Machine Learning Pipeline Application/3. 6.3 - Connecting the Pipeline.mp4 45.35 MB
6. Creating a Machine Learning Pipeline Application/5. 6.4 - Making Predictions with the Model.mp4 44.75 MB
6. Creating a Machine Learning Pipeline Application/6. 6.5 - Data Validation in the Model Package.mp4 32.49 MB
6. Creating a Machine Learning Pipeline Application/7. 6.6 - Feature Engineering in the Pipeline.mp4 26.21 MB
6. Creating a Machine Learning Pipeline Application/8. 6.7 - Versioning and Logging.mp4 70.44 MB
6. Creating a Machine Learning Pipeline Application/9. 6.8 - Building the Package.mp4 75.89 MB
7. Serving the model via REST API/1. 7.1 - Introduction.mp4 25.05 MB
7. Serving the model via REST API/2. 7.2 - Creating the API Skeleton.mp4 35.35 MB
7. Serving the model via REST API/3. 7.2b - Flask Crash Course.mp4 17.81 MB
7. Serving the model via REST API/4. 7.3 - Adding Config and Logging.mp4 33.04 MB
7. Serving the model via REST API/5. 7.4 - Adding the Prediction Endpoint.mp4 38.94 MB
7. Serving the model via REST API/6. 7.5 - Adding a Version Endpoint.mp4 15.41 MB
7. Serving the model via REST API/7. 7.6 - API Schema Validation.mp4 78.1 MB
7. Serving the model via REST API/8. 7.7 - Wrap Up.mp4 6.33 MB
8. Continuous Integration and Deployment Pipelines/1.1 section8.1.mp4.mp4 41.89 MB
8. Continuous Integration and Deployment Pipelines/1. 8.1 - Introduction to CICD.mp4 28.39 MB
8. Continuous Integration and Deployment Pipelines/2. 8.2 - Setting up CircleCI.mp4 10.6 MB
8. Continuous Integration and Deployment Pipelines/3. 8.3 - Setup Circle CI Config.mp4 50.83 MB
8. Continuous Integration and Deployment Pipelines/4. 8.4 - Publishing the Model to Gemfury.mp4 69.12 MB
8. Continuous Integration and Deployment Pipelines/5. 8.5 - Testing the CI Pipeline.mp4 50.13 MB
8. Continuous Integration and Deployment Pipelines/6. 8.6 - Wrap Up.mp4 5.33 MB
9. Differential Testing/1. 9.1 - Introduction.mp4 18.61 MB
9. Differential Testing/2. 9.2 - Setting up Differential Tests.mp4 50.22 MB
9. Differential Testing/3. 9.3 - Differential Tests in CI (Part 1 of 2).mp4 33.56 MB
9. Differential Testing/4. 9.4 - Differential Tests in CI (Part 2 of 2).mp4 32.83 MB
9. Differential Testing/5. 9.5 Wrap Up.mp4 12.68 MB
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