Udemy - Deployment of Machine Learning Models (2.2023)

Creation Time	Oct. 15, 2025, 11:34 a.m.
Last Access Time	Oct. 20, 2025, 6:04 p.m.
File Size	5.1 GB
Keywords	Models of 2023 - Udemy Machine 2 Learning Deployment
Total Requests	36
Total Files	313
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05 - Packaging The Model for Production/003 Code Overview.mp4 173.5 MB
05 - Packaging The Model for Production/007 Working with tox [Do NOT skip - important].mp4 167.4 MB
05 - Packaging The Model for Production/014 Making Predictions with the Package.mp4 143.1 MB
11 - A Deep Learning Model with Big Data/005 Building a CNN in the Research Environment.mp4 143.0 MB
06 - Serving and Deploying the model via REST API/004 The API Endpoints.mp4 137.9 MB
05 - Packaging The Model for Production/010 Package Config.mp4 122.9 MB
04 - Research Environment - Developing a Machine Learning Model/022 Feature engineering with open source demo.mp4 116.6 MB
05 - Packaging The Model for Production/011 The Model Training Script & Pipeline.mp4 115.4 MB
05 - Packaging The Model for Production/015 Building the Package.mp4 114.6 MB
05 - Packaging The Model for Production/004 Understanding the Reasoning Behind the Prod Code Structure.mp4 114.4 MB
11 - A Deep Learning Model with Big Data/010 13.8 - Packaging the CNN.mp4 112.5 MB
04 - Research Environment - Developing a Machine Learning Model/018 Scoring new data with our model.mp4 111.9 MB
04 - Research Environment - Developing a Machine Learning Model/010 Data analysis demo - missing data.mp4 102.9 MB
05 - Packaging The Model for Production/013 Feature Engineering Code in the Package.mp4 95.5 MB
08 - Deploying The ML API With Containers/006 Updating the CI Pipeline for a Container Deployment.mp4 95.3 MB
04 - Research Environment - Developing a Machine Learning Model/015 Feature engineering demo 2.mp4 93.4 MB
07 - Continuous Integration and Deployment Pipelines/006 Using a Private Index Server (Gemfury).mp4 93.2 MB
06 - Serving and Deploying the model via REST API/006 Logging in our Application.mp4 88.9 MB
04 - Research Environment - Developing a Machine Learning Model/014 Feature engineering demo 1.mp4 84.0 MB
04 - Research Environment - Developing a Machine Learning Model/028 Feature engineering pipeline demo.mp4 82.0 MB
13 - Appendix Former Section Serving the model via REST API/009 7.6 - API Schema Validation.mp4 81.2 MB
04 - Research Environment - Developing a Machine Learning Model/020 Python Open Source for Machine Learning.mp4 80.3 MB
11 - A Deep Learning Model with Big Data/006 Production Code for a CNN Learning Pipeline.mp4 79.2 MB
07 - Continuous Integration and Deployment Pipelines/007 Hands on Run the CI Tests in your own Github Fork.mp4 77.9 MB
04 - Research Environment - Developing a Machine Learning Model/012 Data analysis demo - numerical variables.mp4 71.2 MB
06 - Serving and Deploying the model via REST API/012 Deploying our ML Application to Railway - Hands On.mp4 70.9 MB
04 - Research Environment - Developing a Machine Learning Model/027 Create transformers that learn parameters.mp4 70.8 MB
06 - Serving and Deploying the model via REST API/005 Using Schemas in our API.mp4 65.5 MB
02 - Overview of Model Deployment/005 Challenges to Reproducibility.mp4 64.4 MB
10 - Deploying to IaaS (AWS ECS)/011 12.9 - Uploading Images to the Elastic Container Registry (ECR).mp4 63.9 MB
04 - Research Environment - Developing a Machine Learning Model/013 Data analysis demo - categorical variables.mp4 61.8 MB
04 - Research Environment - Developing a Machine Learning Model/031 Getting Ready for Deployment - Final Pipeline.mp4 57.8 MB
08 - Deploying The ML API With Containers/001 Docker Refresher [Optional - For those unfamiliarrusty with Docker].mp4 54.9 MB
09 - Differential Testing/004 9.2 - Setting up Differential Tests.mp4 54.6 MB
04 - Research Environment - Developing a Machine Learning Model/016 Feature selection demo.mp4 52.5 MB
04 - Research Environment - Developing a Machine Learning Model/021 Open Source Libraries for Feature Engineering.mp4 49.1 MB
09 - Differential Testing/002 How to Use the Course Resources.mp4 48.8 MB
04 - Research Environment - Developing a Machine Learning Model/011 Data analysis demo - temporal variables.mp4 47.7 MB
07 - Continuous Integration and Deployment Pipelines/009 Hands on Run the CI Publish on Your Own Github Fork.mp4 46.5 MB
05 - Packaging The Model for Production/012 Introduction to Pytest [Optional].mp4 46.1 MB
11 - A Deep Learning Model with Big Data/011 13.9 - Adding the CNN to the API.mp4 44.0 MB
09 - Differential Testing/005 9.3 - Differential Tests in CI (Part 1 of 2).mp4 43.0 MB
13 - Appendix Former Section Serving the model via REST API/004 7.2 - Creating the API Skeleton.mp4 42.9 MB
13 - Appendix Former Section Serving the model via REST API/007 7.4 - Adding the Prediction Endpoint.mp4 41.2 MB
05 - Packaging The Model for Production/016 Tooling.mp4 41.0 MB
07 - Continuous Integration and Deployment Pipelines/004 CICD Config Explanation.mp4 40.8 MB
01 - Introduction/002 Course curriculum overview.mp4 38.8 MB
06 - Serving and Deploying the model via REST API/003 Introduction to FastAPI.mp4 38.7 MB
08 - Deploying The ML API With Containers/005 Hands On Containerising the App Locally.mp4 38.2 MB
07 - Continuous Integration and Deployment Pipelines/008 Hands on Run the CI Deploy on Your Own Github Fork.mp4 37.5 MB
06 - Serving and Deploying the model via REST API/001 Running the API Locally.mp4 37.4 MB
04 - Research Environment - Developing a Machine Learning Model/017 Model training demo.mp4 35.7 MB
04 - Research Environment - Developing a Machine Learning Model/003 Feature Engineering - Variable Characteristics.mp4 35.5 MB
04 - Research Environment - Developing a Machine Learning Model/004 Feature Engineering Techniques.mp4 35.2 MB
10 - Deploying to IaaS (AWS ECS)/013 12.11 - Updating the Cluster Containers.mp4 35.0 MB
05 - Packaging The Model for Production/006 Package Requirements Files.mp4 34.6 MB
09 - Differential Testing/006 9.4 - Differential Tests in CI (Part 2 of 2).mp4 34.5 MB
04 - Research Environment - Developing a Machine Learning Model/001 Research Environment - Process Overview.mp4 33.7 MB
04 - Research Environment - Developing a Machine Learning Model/005 Feature Selection.mp4 31.9 MB
02 - Overview of Model Deployment/006 Streamlining Model Deployment with Open-Source.mp4 31.3 MB
07 - Continuous Integration and Deployment Pipelines/001 Introduction to CICD.mp4 30.6 MB
10 - Deploying to IaaS (AWS ECS)/012 12.10 - Creating the ECS Cluster with Fargate Launch Method.mp4 30.3 MB
04 - Research Environment - Developing a Machine Learning Model/025 Inheritance and the Scikit-learn API.mp4 29.7 MB
04 - Research Environment - Developing a Machine Learning Model/026 Create Scikit-Learn compatible transformers.mp4 29.3 MB
04 - Research Environment - Developing a Machine Learning Model/002 Machine Learning Pipeline Overview.mp4 27.6 MB
03 - Machine Learning System Architecture/002 Specific Challenges of Machine Learning Systems.mp4 27.4 MB
01 - Introduction/010 How to approach the course.mp4 26.5 MB
10 - Deploying to IaaS (AWS ECS)/015 12.13 - Deploying to ECS via the CI pipeline.mp4 26.2 MB
01 - Introduction/003 Course requirements.mp4 25.6 MB
11 - A Deep Learning Model with Big Data/004 Introduction to a Large Dataset - Plant Seedlings Images.mp4 25.5 MB
10 - Deploying to IaaS (AWS ECS)/003 12.2 - AWS Costs and Caution.mp4 25.4 MB
07 - Continuous Integration and Deployment Pipelines/005 CICD Automation Overview Part 2.mp4 25.4 MB
13 - Appendix Former Section Serving the model via REST API/006 7.3 - Adding Config and Logging.mp4 25.3 MB
03 - Machine Learning System Architecture/004 Machine Learning System Architecture Approaches.mp4 25.1 MB
04 - Research Environment - Developing a Machine Learning Model/024 Intro to Object Oriented Programing.mp4 22.7 MB
10 - Deploying to IaaS (AWS ECS)/009 12.7 - Configuring the AWS CLI.mp4 21.7 MB
10 - Deploying to IaaS (AWS ECS)/008 12.6 - Installing the AWS CLI.mp4 21.5 MB
03 - Machine Learning System Architecture/003 Principles for Machine Learning Systems.mp4 21.0 MB
13 - Appendix Former Section Serving the model via REST API/003 Primer on Monorepos.mp4 19.8 MB
01 - Introduction/001 Introduction to the course.mp4 18.7 MB
11 - A Deep Learning Model with Big Data/007 Reproducibility in Neural Networks.mp4 17.6 MB
08 - Deploying The ML API With Containers/002 The Value of Docker and Containers.mp4 17.2 MB
10 - Deploying to IaaS (AWS ECS)/007 12.5 - Setting Permissions with IAM.mp4 16.9 MB
13 - Appendix Former Section Serving the model via REST API/008 7.5 - Adding a Version Endpoint.mp4 16.8 MB
06 - Serving and Deploying the model via REST API/007 The Uvicorn Web Server.mp4 16.7 MB
02 - Overview of Model Deployment/001 Deployments of Machine Learning Models.mp4 16.5 MB
10 - Deploying to IaaS (AWS ECS)/005 12.3b - Container Orchestration Options Kubernetes, ECS, Docker Swarm.mp4 15.8 MB
10 - Deploying to IaaS (AWS ECS)/002 12.1 - Introduction to AWS.mp4 15.1 MB
10 - Deploying to IaaS (AWS ECS)/004 12.3a - Intro to AWS ECS.mp4 14.9 MB
03 - Machine Learning System Architecture/005 Machine Learning System Component Breakdown.mp4 14.8 MB
02 - Overview of Model Deployment/002 Deployment of Machine Learning Pipelines.mp4 14.0 MB
02 - Overview of Model Deployment/004 Building Reproducible Machine Learning Pipelines.mp4 13.8 MB
13 - Appendix Former Section Serving the model via REST API/002 7.1 - Introduction.mp4 12.5 MB
10 - Deploying to IaaS (AWS ECS)/016 12.14 - Wrap Up.mp4 12.2 MB
06 - Serving and Deploying the model via REST API/002 Understanding the Architecture of the API.mp4 12.0 MB
06 - Serving and Deploying the model via REST API/009 What Is a Platform as a Service (PaaS).mp4 11.6 MB
06 - Serving and Deploying the model via REST API/010 Why Use Railway as Our PaaS.mp4 10.8 MB
11 - A Deep Learning Model with Big Data/012 13.10 - Additional Considerations and Wrap Up.mp4 10.0 MB
09 - Differential Testing/007 9.5 Wrap Up.mp4 8.9 MB
05 - Packaging The Model for Production/001 Introduction to Production Code.mp4 8.8 MB
09 - Differential Testing/003 9.1 - Introduction.mp4 8.6 MB
03 - Machine Learning System Architecture/001 Machine Learning System Architecture and Why it Matters.mp4 7.9 MB
04 - Research Environment - Developing a Machine Learning Model/029 Should feature selection be part of the pipeline.mp4 7.5 MB
08 - Deploying The ML API With Containers/003 Understanding The Container Deployment Process.mp4 7.4 MB
07 - Continuous Integration and Deployment Pipelines/003 CICD Automation Overview Part 1.mp4 7.2 MB
04 - Research Environment - Developing a Machine Learning Model/006 Training a Machine Learning Model.mp4 7.2 MB
07 - Continuous Integration and Deployment Pipelines/002 Setting up CircleCI.mp4 7.0 MB
02 - Overview of Model Deployment/003 Research and Production Environment.mp4 6.2 MB
11 - A Deep Learning Model with Big Data/001 Challenges of using Big Data in Machine Learning.mp4 6.0 MB
10 - Deploying to IaaS (AWS ECS)/010 12.8 - Intro the Elastic Container Registry (ECR).mp4 5.7 MB
01 - Introduction/005 Course Material.mp4 5.3 MB
10 - Deploying to IaaS (AWS ECS)/014 12.12 - Tearing down the ECS Cluster.mp4 4.5 MB
13 - Appendix Former Section Serving the model via REST API/010 7.7 - Wrap Up.mp4 3.9 MB
06 - Serving and Deploying the model via REST API/013 Limitations to Be Aware Of & Wrap Up.mp4 3.7 MB
10 - Deploying to IaaS (AWS ECS)/006 12.4 - Create an AWS Account.mp4 3.2 MB
11 - A Deep Learning Model with Big Data/005 CNN-Analysis-and-Model.zip 1.5 MB
06 - Serving and Deploying the model via REST API/008 Introducing Railway App and Platform as a Service.mp4 1.4 MB
05 - Packaging The Model for Production/003 DMLM-notebook-to-code-diagram.jpeg 788.4 KB
08 - Deploying The ML API With Containers/001 docker-notes.pdf 371.6 KB
03 - Machine Learning System Architecture/003 03.3-Notes.pdf 315.6 KB
03 - Machine Learning System Architecture/004 03.4-Notes.pdf 313.2 KB
03 - Machine Learning System Architecture/002 03.2-Notes.pdf 309.6 KB
12 - Common Issues found during deployment/001 Troubleshooting.pdf 223.4 KB
13 - Appendix Former Section Serving the model via REST API/004 Section7.2-Notes.pdf 146.3 KB
09 - Differential Testing/006 Section9.4-Notes.pdf 100.6 KB
09 - Differential Testing/002 Section5.3a-Notes.pdf 85.5 KB
13 - Appendix Former Section Serving the model via REST API/008 Section7.5-Notes.pdf 84.3 KB
13 - Appendix Former Section Serving the model via REST API/009 Section7.6-Notes.pdf 83.7 KB
13 - Appendix Former Section Serving the model via REST API/006 Section7.3-Notes.pdf 83.1 KB
10 - Deploying to IaaS (AWS ECS)/009 Section12.7-Notes.pdf 83.0 KB
13 - Appendix Former Section Serving the model via REST API/007 Section7.4-Notes.pdf 81.5 KB
10 - Deploying to IaaS (AWS ECS)/003 Section12.2-Notes.pdf 74.7 KB
10 - Deploying to IaaS (AWS ECS)/011 Section12.9-Notes.pdf 72.4 KB
11 - A Deep Learning Model with Big Data/010 Section13.8-Notes.pdf 71.6 KB
09 - Differential Testing/007 Section9.5-Notes.pdf 69.5 KB
10 - Deploying to IaaS (AWS ECS)/013 Section12.12-Notes.pdf 67.5 KB
09 - Differential Testing/004 Section9.2-Notes.pdf 64.9 KB
10 - Deploying to IaaS (AWS ECS)/015 Section12.14-Notes.pdf 64.2 KB
13 - Appendix Former Section Serving the model via REST API/002 Section7.1-Notes.pdf 63.4 KB
10 - Deploying to IaaS (AWS ECS)/014 Section12.13-Notes.pdf 60.1 KB
11 - A Deep Learning Model with Big Data/012 Section13.10-Notes.pdf 60.0 KB
10 - Deploying to IaaS (AWS ECS)/007 Section12.5-Notes.pdf 57.9 KB
10 - Deploying to IaaS (AWS ECS)/008 Section12.6-Notes.pdf 56.9 KB
10 - Deploying to IaaS (AWS ECS)/012 Section12.10-Notes.pdf 56.9 KB
10 - Deploying to IaaS (AWS ECS)/016 Section12.15-Notes.pdf 56.6 KB
10 - Deploying to IaaS (AWS ECS)/010 Section12.8-Notes.pdf 55.3 KB
10 - Deploying to IaaS (AWS ECS)/004 Section12.3-Notes.pdf 55.1 KB
10 - Deploying to IaaS (AWS ECS)/005 Section12.3-Notes.pdf 55.1 KB
13 - Appendix Former Section Serving the model via REST API/003 Section5.3c-Notes.pdf 53.9 KB
10 - Deploying to IaaS (AWS ECS)/006 Section12.4-Notes.pdf 53.5 KB
11 - A Deep Learning Model with Big Data/011 Section13.9-Notes.pdf 53.2 KB
05 - Packaging The Model for Production/003 Code Overview.srt 16.2 KB
05 - Packaging The Model for Production/004 Understanding the Reasoning Behind the Prod Code Structure.srt 16.0 KB
04 - Research Environment - Developing a Machine Learning Model/020 Python Open Source for Machine Learning.srt 13.5 KB
04 - Research Environment - Developing a Machine Learning Model/010 Data analysis demo - missing data.srt 13.2 KB
05 - Packaging The Model for Production/007 Working with tox [Do NOT skip - important].srt 12.9 KB
02 - Overview of Model Deployment/005 Challenges to Reproducibility.srt 12.8 KB
06 - Serving and Deploying the model via REST API/004 The API Endpoints.srt 12.7 KB
04 - Research Environment - Developing a Machine Learning Model/022 Feature engineering with open source demo.srt 12.6 KB
04 - Research Environment - Developing a Machine Learning Model/018 Scoring new data with our model.srt 12.5 KB
04 - Research Environment - Developing a Machine Learning Model/005 Feature Selection.srt 12.3 KB
05 - Packaging The Model for Production/012 Introduction to Pytest [Optional].srt 12.3 KB
07 - Continuous Integration and Deployment Pipelines/004 CICD Config Explanation.srt 11.7 KB
05 - Packaging The Model for Production/014 Making Predictions with the Package.srt 11.1 KB
11 - A Deep Learning Model with Big Data/005 Building a CNN in the Research Environment.srt 10.8 KB
11 - A Deep Learning Model with Big Data/006 Production Code for a CNN Learning Pipeline.srt 10.7 KB
06 - Serving and Deploying the model via REST API/012 Deploying our ML Application to Railway - Hands On.srt 10.7 KB
04 - Research Environment - Developing a Machine Learning Model/014 Feature engineering demo 1.srt 10.5 KB
05 - Packaging The Model for Production/010 Package Config.srt 10.2 KB
04 - Research Environment - Developing a Machine Learning Model/015 Feature engineering demo 2.srt 10.0 KB
03 - Machine Learning System Architecture/003 Principles for Machine Learning Systems.srt 9.9 KB
04 - Research Environment - Developing a Machine Learning Model/012 Data analysis demo - numerical variables.srt 9.6 KB
03 - Machine Learning System Architecture/004 Machine Learning System Architecture Approaches.srt 9.4 KB
07 - Continuous Integration and Deployment Pipelines/008 Hands on Run the CI Deploy on Your Own Github Fork.srt 9.4 KB
05 - Packaging The Model for Production/013 Feature Engineering Code in the Package.srt 9.3 KB
04 - Research Environment - Developing a Machine Learning Model/003 Feature Engineering - Variable Characteristics.srt 9.3 KB
06 - Serving and Deploying the model via REST API/003 Introduction to FastAPI.srt 9.2 KB
05 - Packaging The Model for Production/011 The Model Training Script & Pipeline.srt 8.9 KB
08 - Deploying The ML API With Containers/006 Updating the CI Pipeline for a Container Deployment.srt 8.6 KB
05 - Packaging The Model for Production/015 Building the Package.srt 8.5 KB
04 - Research Environment - Developing a Machine Learning Model/013 Data analysis demo - categorical variables.srt 8.4 KB
04 - Research Environment - Developing a Machine Learning Model/028 Feature engineering pipeline demo.srt 8.3 KB
13 - Appendix Former Section Serving the model via REST API/009 7.6 - API Schema Validation.srt 8.2 KB
08 - Deploying The ML API With Containers/002 The Value of Docker and Containers.srt 8.1 KB
07 - Continuous Integration and Deployment Pipelines/006 Using a Private Index Server (Gemfury).srt 8.1 KB
04 - Research Environment - Developing a Machine Learning Model/024 Intro to Object Oriented Programing.srt 8.1 KB
08 - Deploying The ML API With Containers/001 Docker Refresher [Optional - For those unfamiliarrusty with Docker].srt 8.0 KB
04 - Research Environment - Developing a Machine Learning Model/021 Open Source Libraries for Feature Engineering.srt 8.0 KB
03 - Machine Learning System Architecture/005 Machine Learning System Component Breakdown.srt 7.8 KB
04 - Research Environment - Developing a Machine Learning Model/031 Getting Ready for Deployment - Final Pipeline.srt 7.7 KB
07 - Continuous Integration and Deployment Pipelines/005 CICD Automation Overview Part 2.srt 7.7 KB
06 - Serving and Deploying the model via REST API/006 Logging in our Application.srt 7.5 KB
06 - Serving and Deploying the model via REST API/005 Using Schemas in our API.srt 7.5 KB
04 - Research Environment - Developing a Machine Learning Model/004 Feature Engineering Techniques.srt 7.5 KB
02 - Overview of Model Deployment/006 Streamlining Model Deployment with Open-Source.srt 7.4 KB
11 - A Deep Learning Model with Big Data/010 13.8 - Packaging the CNN.srt 7.4 KB
01 - Introduction/002 Course curriculum overview.srt 7.2 KB
04 - Research Environment - Developing a Machine Learning Model/027 Create transformers that learn parameters.srt 7.0 KB
04 - Research Environment - Developing a Machine Learning Model/001 Research Environment - Process Overview.srt 6.9 KB
04 - Research Environment - Developing a Machine Learning Model/002 Machine Learning Pipeline Overview.srt 6.8 KB
04 - Research Environment - Developing a Machine Learning Model/026 Create Scikit-Learn compatible transformers.srt 6.6 KB
02 - Overview of Model Deployment/004 Building Reproducible Machine Learning Pipelines.srt 6.3 KB
06 - Serving and Deploying the model via REST API/001 Running the API Locally.srt 6.3 KB
01 - Introduction/010 How to approach the course.srt 6.0 KB
06 - Serving and Deploying the model via REST API/002 Understanding the Architecture of the API.srt 6.0 KB
03 - Machine Learning System Architecture/002 Specific Challenges of Machine Learning Systems.srt 5.8 KB
08 - Deploying The ML API With Containers/005 Hands On Containerising the App Locally.srt 5.7 KB
04 - Research Environment - Developing a Machine Learning Model/025 Inheritance and the Scikit-learn API.srt 5.7 KB
04 - Research Environment - Developing a Machine Learning Model/011 Data analysis demo - temporal variables.srt 5.6 KB
05 - Packaging The Model for Production/006 Package Requirements Files.srt 5.6 KB
04 - Research Environment - Developing a Machine Learning Model/016 Feature selection demo.srt 5.5 KB
02 - Overview of Model Deployment/002 Deployment of Machine Learning Pipelines.srt 5.3 KB
10 - Deploying to IaaS (AWS ECS)/012 12.10 - Creating the ECS Cluster with Fargate Launch Method.srt 5.2 KB
10 - Deploying to IaaS (AWS ECS)/004 12.3a - Intro to AWS ECS.srt 5.2 KB
01 - Introduction/003 Course requirements.srt 5.1 KB
04 - Research Environment - Developing a Machine Learning Model/017 Model training demo.srt 5.1 KB
10 - Deploying to IaaS (AWS ECS)/011 12.9 - Uploading Images to the Elastic Container Registry (ECR).srt 5.0 KB
06 - Serving and Deploying the model via REST API/010 Why Use Railway as Our PaaS.srt 4.9 KB
07 - Continuous Integration and Deployment Pipelines/001 Introduction to CICD.srt 4.9 KB
13 - Appendix Former Section Serving the model via REST API/006 7.3 - Adding Config and Logging.srt 4.9 KB
13 - Appendix Former Section Serving the model via REST API/004 7.2 - Creating the API Skeleton.srt 4.9 KB
05 - Packaging The Model for Production/016 Tooling.srt 4.7 KB
11 - A Deep Learning Model with Big Data/006 CNNProdCode.zip 4.7 KB
07 - Continuous Integration and Deployment Pipelines/007 Hands on Run the CI Tests in your own Github Fork.srt 4.6 KB
03 - Machine Learning System Architecture/006 Additional Reading Resources.html 4.6 KB
06 - Serving and Deploying the model via REST API/007 The Uvicorn Web Server.srt 4.5 KB
13 - Appendix Former Section Serving the model via REST API/007 7.4 - Adding the Prediction Endpoint.srt 4.5 KB
10 - Deploying to IaaS (AWS ECS)/013 12.11 - Updating the Cluster Containers.srt 4.3 KB
13 - Appendix Former Section Serving the model via REST API/002 7.1 - Introduction.srt 4.3 KB
11 - A Deep Learning Model with Big Data/007 Reproducibility in Neural Networks.srt 4.2 KB
09 - Differential Testing/006 9.4 - Differential Tests in CI (Part 2 of 2).srt 4.2 KB
02 - Overview of Model Deployment/001 Deployments of Machine Learning Models.srt 4.2 KB
11 - A Deep Learning Model with Big Data/011 13.9 - Adding the CNN to the API.srt 4.2 KB
05 - Packaging The Model for Production/001 Introduction to Production Code.srt 4.1 KB
09 - Differential Testing/004 9.2 - Setting up Differential Tests.srt 4.1 KB
10 - Deploying to IaaS (AWS ECS)/005 12.3b - Container Orchestration Options Kubernetes, ECS, Docker Swarm.srt 4.0 KB
09 - Differential Testing/002 How to Use the Course Resources.srt 4.0 KB
04 - Research Environment - Developing a Machine Learning Model/032 Bonus Additional Resources on Scikit-Learn.html 3.9 KB
06 - Serving and Deploying the model via REST API/009 What Is a Platform as a Service (PaaS).srt 3.9 KB
03 - Machine Learning System Architecture/001 Machine Learning System Architecture and Why it Matters.srt 3.8 KB
10 - Deploying to IaaS (AWS ECS)/007 12.5 - Setting Permissions with IAM.srt 3.8 KB
04 - Research Environment - Developing a Machine Learning Model/029 Should feature selection be part of the pipeline.srt 3.8 KB
10 - Deploying to IaaS (AWS ECS)/002 12.1 - Introduction to AWS.srt 3.7 KB
07 - Continuous Integration and Deployment Pipelines/003 CICD Automation Overview Part 1.srt 3.7 KB
11 - A Deep Learning Model with Big Data/008 Setting the Seed for Keras.html 3.7 KB
01 - Introduction/001 Introduction to the course.srt 3.6 KB
11 - A Deep Learning Model with Big Data/012 13.10 - Additional Considerations and Wrap Up.srt 3.6 KB
09 - Differential Testing/005 9.3 - Differential Tests in CI (Part 1 of 2).srt 3.6 KB
04 - Research Environment - Developing a Machine Learning Model/006 Training a Machine Learning Model.srt 3.4 KB
08 - Deploying The ML API With Containers/003 Understanding The Container Deployment Process.srt 3.3 KB
10 - Deploying to IaaS (AWS ECS)/009 12.7 - Configuring the AWS CLI.srt 3.2 KB
05 - Packaging The Model for Production/009 Troubleshooting Tox.html 3.1 KB
07 - Continuous Integration and Deployment Pipelines/009 Hands on Run the CI Publish on Your Own Github Fork.srt 3.0 KB
10 - Deploying to IaaS (AWS ECS)/015 12.13 - Deploying to ECS via the CI pipeline.srt 3.0 KB
09 - Differential Testing/003 9.1 - Introduction.srt 2.9 KB
10 - Deploying to IaaS (AWS ECS)/008 12.6 - Installing the AWS CLI.srt 2.8 KB
06 - Serving and Deploying the model via REST API/014 Section Notes & Further Reading.html 2.8 KB
11 - A Deep Learning Model with Big Data/001 Challenges of using Big Data in Machine Learning.srt 2.8 KB
10 - Deploying to IaaS (AWS ECS)/003 12.2 - AWS Costs and Caution.srt 2.7 KB
02 - Overview of Model Deployment/003 Research and Production Environment.srt 2.4 KB
01 - Introduction/009 Additional Resources for the required skills.html 2.4 KB
09 - Differential Testing/007 9.5 Wrap Up.srt 2.3 KB
13 - Appendix Former Section Serving the model via REST API/003 Primer on Monorepos.srt 2.2 KB
11 - A Deep Learning Model with Big Data/004 Introduction to a Large Dataset - Plant Seedlings Images.srt 2.2 KB
13 - Appendix Former Section Serving the model via REST API/008 7.5 - Adding a Version Endpoint.srt 2.2 KB
10 - Deploying to IaaS (AWS ECS)/016 12.14 - Wrap Up.srt 2.2 KB
01 - Introduction/005 Course Material.srt 2.1 KB
06 - Serving and Deploying the model via REST API/013 Limitations to Be Aware Of & Wrap Up.srt 2.1 KB
07 - Continuous Integration and Deployment Pipelines/002 Setting up CircleCI.srt 1.8 KB
11 - A Deep Learning Model with Big Data/002 Installing Keras.html 1.8 KB
07 - Continuous Integration and Deployment Pipelines/010 Section Notes & Further Reading.html 1.7 KB
04 - Research Environment - Developing a Machine Learning Model/external-links.txt 1.7 KB
13 - Appendix Former Section Serving the model via REST API/010 7.7 - Wrap Up.srt 1.4 KB
05 - Packaging The Model for Production/017 Section Notes & Further Reading.html 1.3 KB
10 - Deploying to IaaS (AWS ECS)/010 12.8 - Intro the Elastic Container Registry (ECR).srt 1.3 KB
01 - Introduction/006 The code.html 1.3 KB
01 - Introduction/008 Download Dataset.html 1.2 KB
02 - Overview of Model Deployment/007 Additional Reading Resources.html 1.1 KB
11 - A Deep Learning Model with Big Data/003 Download the data set.html 905 bytes
01 - Introduction/004 Setting up your computer.html 900 bytes
13 - Appendix Former Section Serving the model via REST API/005 7.2b - Note On Flask.html 859 bytes
13 - Appendix Former Section Serving the model via REST API/001 Appendix - PLEASE READ.html 858 bytes
10 - Deploying to IaaS (AWS ECS)/014 12.12 - Tearing down the ECS Cluster.srt 834 bytes
10 - Deploying to IaaS (AWS ECS)/001 Attention!!! We are currently updating this section.html 825 bytes
09 - Differential Testing/001 Attention !!! - This section still works with old version of code.html 774 bytes
05 - Packaging The Model for Production/005 Reminder Download the Kaggle Data.html 759 bytes
06 - Serving and Deploying the model via REST API/008 Introducing Railway App and Platform as a Service.srt 683 bytes
14 - Final Section/002 Bonus lecture.html 629 bytes
04 - Research Environment - Developing a Machine Learning Model/009 Python library versions.html 619 bytes
10 - Deploying to IaaS (AWS ECS)/006 12.4 - Create an AWS Account.srt 609 bytes
14 - Final Section/001 Congratulations.html 594 bytes
05 - Packaging The Model for Production/008 Migrating from Tox 3 to Tox 4.html 559 bytes
06 - Serving and Deploying the model via REST API/011 Railway Links.html 553 bytes
08 - Deploying The ML API With Containers/004 Docker Install Setup.html 513 bytes
04 - Research Environment - Developing a Machine Learning Model/008 Code covered in this section.html 466 bytes
05 - Packaging The Model for Production/002 Repo for this section.html 454 bytes
11 - A Deep Learning Model with Big Data/009 Seed for Neural Networks - Additional reading resources.html 397 bytes
04 - Research Environment - Developing a Machine Learning Model/030 Research environment - final section.html 395 bytes
04 - Research Environment - Developing a Machine Learning Model/007 Research environment - second part.html 304 bytes
01 - Introduction/007 Presentations.html 303 bytes
04 - Research Environment - Developing a Machine Learning Model/019 Research environment - third part.html 291 bytes
04 - Research Environment - Developing a Machine Learning Model/023 Research environment - fourth part.html 288 bytes
08 - Deploying The ML API With Containers/007 Section Notes & Further Reading.html 245 bytes
04 - Research Environment - Developing a Machine Learning Model/014 Engineering-notebook.url 191 bytes
04 - Research Environment - Developing a Machine Learning Model/015 Engineering-notebook.url 191 bytes
04 - Research Environment - Developing a Machine Learning Model/016 Feature-selection-notebook.url 189 bytes
04 - Research Environment - Developing a Machine Learning Model/017 Model-training-notebook.url 186 bytes
04 - Research Environment - Developing a Machine Learning Model/010 Jupyter-notebook-in-repo.url 185 bytes
04 - Research Environment - Developing a Machine Learning Model/011 Jupyter-notebook-in-repo.url 185 bytes
04 - Research Environment - Developing a Machine Learning Model/012 Jupyter-notebook-in-repo.url 185 bytes
04 - Research Environment - Developing a Machine Learning Model/013 Jupyter-notebook-in-repo.url 185 bytes
04 - Research Environment - Developing a Machine Learning Model/031 link-to-Jupyter-notebook.url 177 bytes
12 - Common Issues found during deployment/001 Troubleshooting.html 105 bytes

Udemy - Deployment of Machine Learning Models (2.2023)

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