Udemy - Ultimate DevOps to MLOps Bootcamp - Build ML CICD Pipelines (8.2025)
大小6.45 GB
文件数200
Info Hash:B34DB49CA249864CBBC08D66A14FB5325C4199A1
收录时间2025-12-27 01:45:31
更新时间2025-12-27 01:45:31
文件列表 (200)
01. About this Course/1. Understand the MLOps Project you will Build in the Course.mp4
10.81 MB
01. About this Course/1. Understand the MLOps Project you will Build in the Course.vtt
9.7 KB
01. About this Course/2. Join RealOps Builders Community on Discord.html
274 B
02. Conceptual Introduction to MLOps/1. M101v2-What-is-MLOps.pdf
2.42 MB
02. Conceptual Introduction to MLOps/1. What is MLOps.mp4
57.25 MB
02. Conceptual Introduction to MLOps/1. What is MLOps.vtt
28.74 KB
02. Conceptual Introduction to MLOps/2. M102-Story-of-AI-Infrastructure-Ops.pdf
4.3 MB
02. Conceptual Introduction to MLOps/2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.mp4
308.4 MB
02. Conceptual Introduction to MLOps/2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.vtt
22.12 KB
02. Conceptual Introduction to MLOps/3. Comparing Three Approaches to AI.mp4
350.94 MB
02. Conceptual Introduction to MLOps/3. Comparing Three Approaches to AI.vtt
29.51 KB
02. Conceptual Introduction to MLOps/3. M103-Understanding-ML-LLM-Agentic-AI.pdf
3.47 MB
02. Conceptual Introduction to MLOps/4. M104-Case-Studies.pdf
3.59 MB
02. Conceptual Introduction to MLOps/4. MLOps Case Studies – Learning from the Pioneers.mp4
123.99 MB
02. Conceptual Introduction to MLOps/4. MLOps Case Studies – Learning from the Pioneers.vtt
16.1 KB
02. Conceptual Introduction to MLOps/5. Comparing Devops vs MLOps.mp4
287.07 MB
02. Conceptual Introduction to MLOps/5. Comparing Devops vs MLOps.vtt
28.53 KB
02. Conceptual Introduction to MLOps/5. M106-MLOps-vs-DevOps-Understanding-the-Evolution.pdf
2.48 MB
02. Conceptual Introduction to MLOps/6. Emergence of MLOps Engineer.mp4
229.53 MB
02. Conceptual Introduction to MLOps/6. Emergence of MLOps Engineer.vtt
20.21 KB
02. Conceptual Introduction to MLOps/6. M105-The-Emergence-of-the-MLOps-Engineer.pdf
2.95 MB
03. Use Case and Environment Setup/1. Module Intro.mp4
65.98 MB
03. Use Case and Environment Setup/1. Module Intro.vtt
4.16 KB
03. Use Case and Environment Setup/10. Working with Jupyter Notebooks.mp4
68.44 MB
03. Use Case and Environment Setup/10. Working with Jupyter Notebooks.vtt
8.47 KB
03. Use Case and Environment Setup/11. Download the Lab Guide.html
91 B
03. Use Case and Environment Setup/11. Lab 3 - Environment Setup.pdf
261.76 KB
03. Use Case and Environment Setup/12. Summary.mp4
74.64 MB
03. Use Case and Environment Setup/12. Summary.vtt
5.26 KB
03. Use Case and Environment Setup/2. Use Case - House Price Predictor - Regression.mp4
31.92 MB
03. Use Case and Environment Setup/2. Use Case - House Price Predictor - Regression.vtt
9.68 KB
03. Use Case and Environment Setup/3. Fork and Clone the Repository.html
271 B
03. Use Case and Environment Setup/4. Understanding End to End ML Practices and MLOps.mp4
81.28 MB
03. Use Case and Environment Setup/4. Understanding End to End ML Practices and MLOps.vtt
26.86 KB
03. Use Case and Environment Setup/5. Environment Setup Overview.mp4
68.07 MB
03. Use Case and Environment Setup/5. Environment Setup Overview.vtt
11.84 KB
03. Use Case and Environment Setup/6. Setting up Docker Podman with Compose.mp4
36.55 MB
03. Use Case and Environment Setup/6. Setting up Docker Podman with Compose.vtt
5.98 KB
03. Use Case and Environment Setup/7. Launching MLflow for Experiemnt Tracking.mp4
57.25 MB
03. Use Case and Environment Setup/7. Launching MLflow for Experiemnt Tracking.vtt
9.44 KB
03. Use Case and Environment Setup/8. Understanding the Project Directory and Scaffold.mp4
66.77 MB
03. Use Case and Environment Setup/8. Understanding the Project Directory and Scaffold.vtt
10.06 KB
03. Use Case and Environment Setup/9. Setting up Python Virtual Environment with UV.mp4
42.88 MB
03. Use Case and Environment Setup/9. Setting up Python Virtual Environment with UV.vtt
7.29 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/1. Module Intro.mp4
66.13 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/1. Module Intro.vtt
4.53 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/10. Download the Lab Guide.html
85 B
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/10. Lab 4 - From Data to Model.pdf
146.45 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/11. Module Summary.mp4
70.57 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/11. Module Summary.vtt
4.26 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/2. Learning Data Engineering.mp4
117.28 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/2. Learning Data Engineering.vtt
17.89 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/3. Experimental Data Analysis.mp4
82.09 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/3. Experimental Data Analysis.vtt
10.66 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/4. Understaing Feature Engineering Concepts.mp4
28.18 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/4. Understaing Feature Engineering Concepts.vtt
7.7 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/5. Building New Features for House Price Predictor.mp4
59.78 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/5. Building New Features for House Price Predictor.vtt
6.67 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/6. Preparing for Model Experimentation.mp4
56.02 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/6. Preparing for Model Experimentation.vtt
7.75 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/7. Data Splitting with x_train, y_train, x_test, y_test.mp4
50.99 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/7. Data Splitting with x_train, y_train, x_test, y_test.vtt
6.26 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/8. Defining Algorithms and Hyperparameter Grids.mp4
62.31 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/8. Defining Algorithms and Hyperparameter Grids.vtt
7.36 KB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/9. Running Model Experiments to find the Best Model and Hyperparamters.mp4
105.99 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/9. Running Model Experiments to find the Best Model and Hyperparamters.vtt
11.57 KB
05. Bonus Understanding the Core ML Algorithms/1. Module Intro.mp4
16.36 MB
05. Bonus Understanding the Core ML Algorithms/1. Module Intro.vtt
928 B
05. Bonus Understanding the Core ML Algorithms/2. Linear Regression.mp4
50.35 MB
05. Bonus Understanding the Core ML Algorithms/2. Linear Regression.vtt
6.76 KB
05. Bonus Understanding the Core ML Algorithms/3. Logistic Regression.mp4
26.64 MB
05. Bonus Understanding the Core ML Algorithms/3. Logistic Regression.vtt
4.13 KB
05. Bonus Understanding the Core ML Algorithms/4. Decision Tree.mp4
28.22 MB
05. Bonus Understanding the Core ML Algorithms/4. Decision Tree.vtt
5.55 KB
05. Bonus Understanding the Core ML Algorithms/5. Random Forest.mp4
39.32 MB
05. Bonus Understanding the Core ML Algorithms/5. Random Forest.vtt
6.4 KB
05. Bonus Understanding the Core ML Algorithms/6. Support Vector Machine (SVM).mp4
25.33 MB
05. Bonus Understanding the Core ML Algorithms/6. Support Vector Machine (SVM).vtt
2.92 KB
05. Bonus Understanding the Core ML Algorithms/7. Neural Networking.mp4
45.23 MB
05. Bonus Understanding the Core ML Algorithms/7. Neural Networking.vtt
6.56 KB
05. Bonus Understanding the Core ML Algorithms/8. Boosting Algorithms (XGBoost, LightGBM etc.).mp4
84.57 MB
05. Bonus Understanding the Core ML Algorithms/8. Boosting Algorithms (XGBoost, LightGBM etc.).vtt
10.04 KB
05. Bonus Understanding the Core ML Algorithms/9. Module Summary.mp4
29.58 MB
05. Bonus Understanding the Core ML Algorithms/9. Module Summary.vtt
1.78 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/1. Module Intro.mp4
65.75 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/1. Module Intro.vtt
3.94 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/10. Download the Lab Guide.html
74 B
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/10. Lab 5 - Containerize and Deploy the Model with Streamlit App.pdf
219.52 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/11. Summary.mp4
85.8 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/11. Summary.vtt
5.8 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/2. Handover from Data Scientist to ML Engineer MLOps.mp4
30.43 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/2. Handover from Data Scientist to ML Engineer MLOps.vtt
8.58 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/3. Running Feature Engineering and Preprocessing Jobs.mp4
44.79 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/3. Running Feature Engineering and Preprocessing Jobs.vtt
6.2 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/4. Building and Training Final Model with Configs from Data Scientists.mp4
52.1 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/4. Building and Training Final Model with Configs from Data Scientists.vtt
7.47 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/5. Wrapping the Model with FastAPI with Streamlit Client Apps.mp4
77.62 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/5. Wrapping the Model with FastAPI with Streamlit Client Apps.vtt
9.04 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/6. Writing Dockerfile to package Model with FastAPI Wrapper.mp4
116.67 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/6. Writing Dockerfile to package Model with FastAPI Wrapper.vtt
21.82 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/7. Debugging and Fixing Image Failures, Launch and Validate FastAPI.mp4
96.51 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/7. Debugging and Fixing Image Failures, Launch and Validate FastAPI.vtt
13.41 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/8. Packaging and testing Streamlit App.mp4
67.75 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/8. Packaging and testing Streamlit App.vtt
11.42 KB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/9. Packaging and Model Serving Infra with Docker Compose.mp4
102.73 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/9. Packaging and Model Serving Infra with Docker Compose.vtt
18.23 KB
07. Setting up MLOps CI Workflow with GitHub Actions/1. Moule Intro.mp4
58.04 MB
07. Setting up MLOps CI Workflow with GitHub Actions/1. Moule Intro.vtt
3.62 KB
07. Setting up MLOps CI Workflow with GitHub Actions/10. Download the Lab Guide.html
85 B
07. Setting up MLOps CI Workflow with GitHub Actions/10. Lab 6 - MLOps CI PipelineWorkflow with GitHub Actions.pdf
1.07 MB
07. Setting up MLOps CI Workflow with GitHub Actions/11. Summary.mp4
54 MB
07. Setting up MLOps CI Workflow with GitHub Actions/11. Summary.vtt
3.36 KB
07. Setting up MLOps CI Workflow with GitHub Actions/2. DAGs, GitHub Actions and our MLOps CI Workflow.mp4
53.21 MB
07. Setting up MLOps CI Workflow with GitHub Actions/2. DAGs, GitHub Actions and our MLOps CI Workflow.vtt
17.63 KB
07. Setting up MLOps CI Workflow with GitHub Actions/3. Understanding GitHub Actions Syntax.mp4
57.65 MB
07. Setting up MLOps CI Workflow with GitHub Actions/3. Understanding GitHub Actions Syntax.vtt
10.59 KB
07. Setting up MLOps CI Workflow with GitHub Actions/4. Writing an executung out first GitHub Actions Workflow.mp4
118.71 MB
07. Setting up MLOps CI Workflow with GitHub Actions/4. Writing an executung out first GitHub Actions Workflow.vtt
16.43 KB
07. Setting up MLOps CI Workflow with GitHub Actions/5. Adding Data and Feature Engineering Steps with Model Training.mp4
56.55 MB
07. Setting up MLOps CI Workflow with GitHub Actions/5. Adding Data and Feature Engineering Steps with Model Training.vtt
6.14 KB
07. Setting up MLOps CI Workflow with GitHub Actions/6. Model Training Step with MLFlow for Tracking.mp4
79.43 MB
07. Setting up MLOps CI Workflow with GitHub Actions/6. Model Training Step with MLFlow for Tracking.vtt
7.54 KB
07. Setting up MLOps CI Workflow with GitHub Actions/7. Adding Image Build and Publish Step with Docker.mp4
53.44 MB
07. Setting up MLOps CI Workflow with GitHub Actions/7. Adding Image Build and Publish Step with Docker.vtt
7.22 KB
07. Setting up MLOps CI Workflow with GitHub Actions/8. Configurating Registry Token and publishing Image to DockerHub.mp4
65.19 MB
07. Setting up MLOps CI Workflow with GitHub Actions/8. Configurating Registry Token and publishing Image to DockerHub.vtt
8.46 KB
07. Setting up MLOps CI Workflow with GitHub Actions/9. Modular, Multi Stage MLOps CI Workflow Pipeline.mp4
151.95 MB
07. Setting up MLOps CI Workflow with GitHub Actions/9. Modular, Multi Stage MLOps CI Workflow Pipeline.vtt
17.83 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/1. Module Intro.mp4
41.98 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/1. Module Intro.vtt
2.32 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/10. Easy way to Generate Kubernetes Manifets and YAML.mp4
31.73 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/10. Easy way to Generate Kubernetes Manifets and YAML.vtt
7.96 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/11. Download the Lab Guide.html
86 B
08. Building Scalable Prod Inference Infrastructure with Kubernetes/11. Lab 7 - Deploying to Kubernetes.pdf
51.51 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/12. Summary.mp4
41.5 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/12. Summary.vtt
2.37 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/2. Designing Scalable Infrastructure for Model Inference.mp4
18.52 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/2. Designing Scalable Infrastructure for Model Inference.vtt
5.9 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/3. Introduction to Kubernetes for Machine Learning.mp4
47.41 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/3. Introduction to Kubernetes for Machine Learning.vtt
13.87 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/4. Kubernetes Core Concepts - Pods, Deployments and Services.mp4
39.58 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/4. Kubernetes Core Concepts - Pods, Deployments and Services.vtt
12.08 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/5. Simplest way to build a 3 Node Kubernetes Cluster with KIND.mp4
70.82 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/5. Simplest way to build a 3 Node Kubernetes Cluster with KIND.vtt
12.36 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/6. Deploying Streamlit Frontent App with Kubernetes.mp4
89.83 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/6. Deploying Streamlit Frontent App with Kubernetes.vtt
15.96 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/7. Exposing the Streamlit App with Kubernetes NodePort Service.mp4
44.41 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/7. Exposing the Streamlit App with Kubernetes NodePort Service.vtt
8.23 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/8. Creating Deployment Service for the Model wrapped in FastAPI.mp4
47.69 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/8. Creating Deployment Service for the Model wrapped in FastAPI.vtt
8.02 KB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/9. Connecting Streamlit with Model using Kubernetes native DNS Based Service Discov.mp4
86.65 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/9. Connecting Streamlit with Model using Kubernetes native DNS Based Service Discov.vtt
13.2 KB
09. Monitoring and Autoscaling a ML Model/1. Module Intro.mp4
29.53 MB
09. Monitoring and Autoscaling a ML Model/1. Module Intro.vtt
1.68 KB
09. Monitoring and Autoscaling a ML Model/10. AI Based Troubleshooting Monitoring with ChatGPT.mp4
91.05 MB
09. Monitoring and Autoscaling a ML Model/10. AI Based Troubleshooting Monitoring with ChatGPT.vtt
11.09 KB
09. Monitoring and Autoscaling a ML Model/11. Running Load Test and Analysing Autoscaling.mp4
75.37 MB
09. Monitoring and Autoscaling a ML Model/11. Running Load Test and Analysing Autoscaling.vtt
10.46 KB
09. Monitoring and Autoscaling a ML Model/12. CPU Based Auto Scaling with KEDA.mp4
78.41 MB
09. Monitoring and Autoscaling a ML Model/12. CPU Based Auto Scaling with KEDA.vtt
12.12 KB
09. Monitoring and Autoscaling a ML Model/13. Adding a Verticle Pod Autoscaler (VPA).mp4
92.34 MB
09. Monitoring and Autoscaling a ML Model/13. Adding a Verticle Pod Autoscaler (VPA).vtt
13.5 KB
09. Monitoring and Autoscaling a ML Model/14. Lab - Setting up Monitoring with Prometheus and Grafana.html
79 B
09. Monitoring and Autoscaling a ML Model/14. Lab 8 - Setting up Model Monitoring.pdf
946.84 KB
09. Monitoring and Autoscaling a ML Model/15. Lab - Setting up ML Autoscaling.html
89 B
09. Monitoring and Autoscaling a ML Model/15. Lab 9 - Autoscaling Models.pdf
180.56 KB
09. Monitoring and Autoscaling a ML Model/16. Summary.mp4
49.58 MB
09. Monitoring and Autoscaling a ML Model/16. Summary.vtt
2.85 KB
09. Monitoring and Autoscaling a ML Model/2. Project Spec.mp4
6.66 MB
09. Monitoring and Autoscaling a ML Model/2. Project Spec.vtt
3.31 KB
09. Monitoring and Autoscaling a ML Model/3. Installing Prometheus and Grafana with Helm.mp4
57.28 MB
09. Monitoring and Autoscaling a ML Model/3. Installing Prometheus and Grafana with Helm.vtt
7.85 KB
09. Monitoring and Autoscaling a ML Model/4. Exploring Monitoring Metrics with Grafana and Prometheus.mp4
75.46 MB
09. Monitoring and Autoscaling a ML Model/4. Exploring Monitoring Metrics with Grafana and Prometheus.vtt
10.35 KB
09. Monitoring and Autoscaling a ML Model/5. Adding Instrumentation for FastAPI along with Custom Dashboard.mp4
103.15 MB
09. Monitoring and Autoscaling a ML Model/5. Adding Instrumentation for FastAPI along with Custom Dashboard.vtt
13.31 KB
09. Monitoring and Autoscaling a ML Model/6. Automatic Capacity Scaling Concepts.mp4
34.52 MB
09. Monitoring and Autoscaling a ML Model/6. Automatic Capacity Scaling Concepts.vtt
4.54 KB
09. Monitoring and Autoscaling a ML Model/7. Installing KEDA and Configuring Resource Spec.mp4
42.76 MB
09. Monitoring and Autoscaling a ML Model/7. Installing KEDA and Configuring Resource Spec.vtt
5.91 KB
09. Monitoring and Autoscaling a ML Model/8. Configuring Scaled Objects with KEDA.mp4
61.35 MB
09. Monitoring and Autoscaling a ML Model/8. Configuring Scaled Objects with KEDA.vtt
8.93 KB
09. Monitoring and Autoscaling a ML Model/9. Getting started with Load Testing Model Inference.mp4
64.69 MB
09. Monitoring and Autoscaling a ML Model/9. Getting started with Load Testing Model Inference.vtt
8.4 KB
10. GitOps Based Deployments for MLLLM Apps/1. Module Intro.mp4
14.65 MB
10. GitOps Based Deployments for MLLLM Apps/1. Module Intro.vtt
705 B
10. GitOps Based Deployments for MLLLM Apps/2. GitOps Concepts.mp4
23.2 MB
10. GitOps Based Deployments for MLLLM Apps/2. GitOps Concepts.vtt
6.07 KB
10. GitOps Based Deployments for MLLLM Apps/3. GitOps Pricinple 2 Start Revision Controling the Code.mp4
46.9 MB
10. GitOps Based Deployments for MLLLM Apps/3. GitOps Pricinple 2 Start Revision Controling the Code.vtt
7.72 KB
10. GitOps Based Deployments for MLLLM Apps/4. GitOps Principle 4 Setup a Agent - ArgoCD.mp4
42.87 MB
10. GitOps Based Deployments for MLLLM Apps/4. GitOps Principle 4 Setup a Agent - ArgoCD.vtt
5.27 KB
10. GitOps Based Deployments for MLLLM Apps/5. Overview of Argo Application CRD.mp4
56.67 MB
10. GitOps Based Deployments for MLLLM Apps/5. Overview of Argo Application CRD.vtt
6.54 KB
10. GitOps Based Deployments for MLLLM Apps/6. Continuous Delivery with ArgoCD Applications.mp4
115.91 MB
10. GitOps Based Deployments for MLLLM Apps/6. Continuous Delivery with ArgoCD Applications.vtt
14.4 KB
10. GitOps Based Deployments for MLLLM Apps/7. End to End CI and CD Pielines for ML App.mp4
302.91 MB
10. GitOps Based Deployments for MLLLM Apps/7. End to End CI and CD Pielines for ML App.vtt
26.95 KB
10. GitOps Based Deployments for MLLLM Apps/8. Summary.mp4
63.77 MB
10. GitOps Based Deployments for MLLLM Apps/8. Summary.vtt