Udemy - MLOps Bootcamp Mastering AI Operations for Success - AIOps (7.2024)

Creation Time	Aug. 9, 2025, 5:50 a.m.
Last Access Time	Jan. 18, 2026, 2:45 p.m.
File Size	13.8 GB
Keywords	Operations Success for AI - Bootcamp 2024 7 Mastering MLOps Udemy AIOps
Total Requests	548
Total Files	493
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

11 - Lnux Operating System for DevOps and Data Scientists/004 Basic Linux Commands of Linux.mp4 566.8 MB
21 - Additional Learning on Topic of MLOps/003 Kubernetes 101 Part 2.mp4 428.0 MB
21 - Additional Learning on Topic of MLOps/001 MLOps with MLFlow in 1 Hour.mp4 415.4 MB
17 - Monitor the ML System with WhyLogs/003 Whylogs - Drift Detection, Input, Output, Bias Monitoring.mp4 384.7 MB
21 - Additional Learning on Topic of MLOps/005 Bonus Understanding Transformer Architecture.mp4 383.7 MB
09 - Build MLApps using Streamlit/003 Building the ML Model with Streamlit.mp4 330.0 MB
21 - Additional Learning on Topic of MLOps/004 Generative AI and Prompt Engineering Introduction.mp4 198.4 MB
05 - Packaging the ML Models/002 Typical Experimentation with Dataset.mp4 176.9 MB
05 - Packaging the ML Models/009 Data Preprocessing part 1.mp4 167.4 MB
05 - Packaging the ML Models/007 Create Config Module.mp4 166.1 MB
21 - Additional Learning on Topic of MLOps/002 Kubernetes 101 Part 1.mp4 159.2 MB
06 - Mlflow - Manage ML experiments/008 MLFlow Project.mp4 152.1 MB
15 - Deploy Applications with Docker Compose/002 Hands On - Docker Compose with Flask Application.mp4 148.8 MB
12 - Working with CI CD Tool Jenkins/004 Deploy as API with FASTAPI.mp4 141.4 MB
06 - Mlflow - Manage ML experiments/006 Machine Learning Experiement on MLFlow.mp4 140.2 MB
07 - Docker for Machine Learning/002 Introduction to Docker.mp4 137.6 MB
01 - Introduction to Complete MLOps Bootcamp/003 The Stages of MLOps.mp4 136.3 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/024 Advanced Functions in Pandas DataFrame.mp4 136.3 MB
15 - Deploy Applications with Docker Compose/003 Hands On - Docker Compose Prometheus Grafana.mp4 133.8 MB
12 - Working with CI CD Tool Jenkins/011 Configure Github Repo - Webhook - Jenkins Credentials.mp4 133.6 MB
05 - Packaging the ML Models/026 Packagiing the ML Model & testing.mp4 132.5 MB
11 - Lnux Operating System for DevOps and Data Scientists/002 Linux Features & Bash.mp4 132.4 MB
12 - Working with CI CD Tool Jenkins/019 Create CI CT CD Pipeline - Github Dockerhub.mp4 131.8 MB
07 - Docker for Machine Learning/004 Working with Docker.mp4 130.4 MB
06 - Mlflow - Manage ML experiments/004 Basic Mlflow tutorial.mp4 129.4 MB
16 - Continuous Monitoring of Machine Learning Application/002 Hands On Monitoring of ML Application using Prometheus.mp4 126.1 MB
06 - Mlflow - Manage ML experiments/011 Log Model Metrics in MySql.mp4 124.6 MB
10 - Build MLApps using Flask/002 Hands On Learning of Flask Library.mp4 123.9 MB
08 - Build MLApps using FastAPI/004 Crash course on FastAPI.mp4 122.3 MB
05 - Packaging the ML Models/004 Challenges in Working inside the Jupyter Notebook.mp4 115.6 MB
14 - Continuous Monitoring with Prometheus/006 Installation of Prometheus.mp4 113.9 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/015 Broadcasting on Numpy Arrays.mp4 113.0 MB
09 - Build MLApps using Streamlit/002 Hands On Working with Streamlit.mp4 107.0 MB
05 - Packaging the ML Models/005 Understanding the Modular Programming.mp4 106.6 MB
14 - Continuous Monitoring with Prometheus/014 Monitor the FastAPI Application using Prometheus.mp4 104.7 MB
10 - Build MLApps using Flask/003 Build ML Model App with Flask.mp4 104.2 MB
06 - Mlflow - Manage ML experiments/009 MLFlow Models.mp4 102.7 MB
12 - Working with CI CD Tool Jenkins/017 Setup Email Notification with Gmail.mp4 101.0 MB
05 - Packaging the ML Models/006 Creating Folder Hierarchy for ML Project.mp4 100.7 MB
12 - Working with CI CD Tool Jenkins/008 Test Locally using Docker Containers.mp4 100.5 MB
14 - Continuous Monitoring with Prometheus/017 Trigger Alerts with Grafana.mp4 100.3 MB
12 - Working with CI CD Tool Jenkins/015 Test Github Webhook with Jenkins.mp4 100.2 MB
05 - Packaging the ML Models/011 sklearn pipeline.mp4 99.3 MB
12 - Working with CI CD Tool Jenkins/005 Test FastAPI App.mp4 96.8 MB
07 - Docker for Machine Learning/008 Dockerize the ML Model.mp4 95.5 MB
03 - Git and Github Fundamentals for MLOps/008 Git Branch.mp4 93.9 MB
04 - Crash Course on YAML/001 YAML Crash Course.mp4 91.8 MB
06 - Mlflow - Manage ML experiments/007 Create ML Model for Loan Prediction.mp4 91.4 MB
14 - Continuous Monitoring with Prometheus/012 Monitor the Linux Server with Node Exporter.mp4 90.2 MB
07 - Docker for Machine Learning/006 Working with Dockerfile.mp4 89.5 MB
12 - Working with CI CD Tool Jenkins/001 Introduction to Jenkins.mp4 87.3 MB
05 - Packaging the ML Models/025 Create setup.py.mp4 84.5 MB
12 - Working with CI CD Tool Jenkins/009 Installation of Jenkins on AWS EC2 Instances.mp4 84.2 MB
01 - Introduction to Complete MLOps Bootcamp/001 What and Why MLOps.mp4 82.9 MB
06 - Mlflow - Manage ML experiments/012 Register the Model & Serve the Model.mp4 81.6 MB
07 - Docker for Machine Learning/005 Running the Docker Container.mp4 81.4 MB
05 - Packaging the ML Models/012 Training Pipeline.mp4 80.0 MB
06 - Mlflow - Manage ML experiments/003 Logging Functions of Mlflow Tracking.mp4 77.6 MB
14 - Continuous Monitoring with Prometheus/009 Prometheus Configuration file.mp4 74.6 MB
08 - Build MLApps using FastAPI/002 How REST API Works.mp4 72.9 MB
03 - Git and Github Fundamentals for MLOps/010 Merging.mp4 72.0 MB
08 - Build MLApps using FastAPI/006 Deploying the Machine Learning Model with FastAPI.mp4 70.8 MB
03 - Git and Github Fundamentals for MLOps/015 3 way merge.mp4 70.7 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/042 Univariate & Bivariate Plots - Continuous Data.mp4 69.6 MB
07 - Docker for Machine Learning/009 Packaging the training code in Docker Environment & Summary.mp4 68.5 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/022 Combining the DataFrames.mp4 67.0 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/028 Preliminary Analysis on DataFrame.mp4 66.8 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/041 Exploring the data.mp4 66.4 MB
12 - Working with CI CD Tool Jenkins/016 Installation of Docker Plugin & System Readiness.mp4 64.7 MB
17 - Monitor the ML System with WhyLogs/004 WhyLogs - Constraints and Drift Reports.mp4 64.6 MB
14 - Continuous Monitoring with Prometheus/004 Architecture of Prometheus.mp4 63.5 MB
14 - Continuous Monitoring with Prometheus/010 Exploring the Basic Querying Prometheus.mp4 63.3 MB
03 - Git and Github Fundamentals for MLOps/007 Git Workflow - Local Repo.mp4 62.7 MB
05 - Packaging the ML Models/008 Data Handling Module.mp4 61.4 MB
05 - Packaging the ML Models/022 Running Pytest.mp4 60.0 MB
19 - Reference Getting Started with AWS/014 Launch EC2 instance & SSH into EC2 Instances.mp4 59.9 MB
02 - Python for MLOps/012 Collection - Strings.mp4 58.7 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/023 Other Functions on Pandas DataFrame.mp4 58.0 MB
03 - Git and Github Fundamentals for MLOps/002 Getting Started with git.mp4 57.2 MB
06 - Mlflow - Manage ML experiments/001 Introduction to Mlflow.mp4 57.0 MB
14 - Continuous Monitoring with Prometheus/015 Monitor All EndPoints using Prometheus.mp4 56.9 MB
19 - Reference Getting Started with AWS/007 IAM Policy generator & attachment.mp4 56.1 MB
03 - Git and Github Fundamentals for MLOps/014 Cloning and Delete Branches.mp4 55.8 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/021 Working with Data in Pandas DataFrame.mp4 55.7 MB
03 - Git and Github Fundamentals for MLOps/009 Switching the Branches.mp4 55.0 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/031 Introduction to Data Visualization.mp4 54.9 MB
03 - Git and Github Fundamentals for MLOps/013 Working with Remote Repositories.mp4 54.5 MB
12 - Working with CI CD Tool Jenkins/020 Create CI CT CD Pipeline - Training.mp4 54.3 MB
03 - Git and Github Fundamentals for MLOps/011 Checking Out Commits.mp4 54.2 MB
02 - Python for MLOps/011 Operators in Python Programming Language.mp4 52.5 MB
12 - Working with CI CD Tool Jenkins/003 Prepare and Package ML Model.mp4 51.2 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/029 Null values in the Dataframe.mp4 50.6 MB
03 - Git and Github Fundamentals for MLOps/005 Getting Started with Local Repo.mp4 50.4 MB
19 - Reference Getting Started with AWS/004 Create IAM Account and Account Alias.mp4 50.0 MB
06 - Mlflow - Manage ML experiments/005 Exploration of mlflow.mp4 49.9 MB
13 - Monitoring and Debugging of ML System/005 Functional Level Monitoring.mp4 49.4 MB
14 - Continuous Monitoring with Prometheus/001 Introduction to Continuous Monitoring.mp4 48.0 MB
08 - Build MLApps using FastAPI/001 What is API, REST and REST API.mp4 47.8 MB
05 - Packaging the ML Models/001 Introduction to Packaging the ML Models.mp4 47.4 MB
17 - Monitor the ML System with WhyLogs/001 Introduction to ML Monitoring.mp4 46.8 MB
02 - Python for MLOps/010 Python Literals - Hands On.mp4 45.8 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/027 Loading the Large Dataset for Working.mp4 45.4 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/007 Array Creation Functions.mp4 45.1 MB
14 - Continuous Monitoring with Prometheus/016 Create Visualization with Grafana.mp4 44.3 MB
05 - Packaging the ML Models/013 Prediction Pipeline.mp4 44.0 MB
19 - Reference Getting Started with AWS/009 S3 Bucket and Storage Classes.mp4 43.9 MB
12 - Working with CI CD Tool Jenkins/022 Create CI CT CD Pipeline - Deployment.mp4 43.5 MB
12 - Working with CI CD Tool Jenkins/021 Create CI CT CD Pipeline - Testing.mp4 43.2 MB
13 - Monitoring and Debugging of ML System/003 Why Monitoring Machine Learning Models is Difficult.mp4 43.2 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/038 Scatter Plot hands on.mp4 43.1 MB
02 - Python for MLOps/027 File Handling in Python.mp4 43.0 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/018 Working with Pandas Series.mp4 43.0 MB
05 - Packaging the ML Models/019 Requirements txt file.mp4 42.6 MB
05 - Packaging the ML Models/021 Create Python tests.mp4 42.5 MB
06 - Mlflow - Manage ML experiments/010 Setting Up MySql Database Locally.mp4 41.5 MB
02 - Python for MLOps/024 Functions.mp4 40.9 MB
05 - Packaging the ML Models/027 Summary.mp4 40.8 MB
12 - Working with CI CD Tool Jenkins/010 Installation of Docker in EC2 Instance.mp4 40.7 MB
19 - Reference Getting Started with AWS/002 Create AWS Account.mp4 38.9 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/011 Shape Modification of Arrays.mp4 38.9 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/043 Plot - Categorical Data.mp4 38.8 MB
14 - Continuous Monitoring with Prometheus/008 Installation of Grafana.mp4 38.0 MB
02 - Python for MLOps/014 Data Structures - List.mp4 36.7 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/034 Line Plots Hands On.mp4 36.6 MB
03 - Git and Github Fundamentals for MLOps/001 Introduction to Version Control Systems.mp4 34.7 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/001 Introduction to Numpy Library.mp4 34.7 MB
02 - Python for MLOps/022 Control Statements - Looping Statements.mp4 34.5 MB
06 - Mlflow - Manage ML experiments/002 Getting System Ready with mlflow.mp4 34.5 MB
03 - Git and Github Fundamentals for MLOps/012 Git Hosting Services.mp4 34.0 MB
19 - Reference Getting Started with AWS/012 Version Enablement in S3.mp4 33.6 MB
13 - Monitoring and Debugging of ML System/006 Model Drift.mp4 33.6 MB
08 - Build MLApps using FastAPI/003 What is FastAPI.mp4 32.2 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/036 Plot Adjustment Hands On.mp4 32.1 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/020 Dataframes in Pandas.mp4 32.0 MB
19 - Reference Getting Started with AWS/013 Introduction EC2 instances.mp4 31.9 MB
16 - Continuous Monitoring of Machine Learning Application/001 Architecture of ML Application Monitoring.mp4 31.4 MB
02 - Python for MLOps/005 Hello World - Python.mp4 31.1 MB
12 - Working with CI CD Tool Jenkins/024 Summary.mp4 31.0 MB
19 - Reference Getting Started with AWS/003 Setting up MFA on Root Account.mp4 30.7 MB
05 - Packaging the ML Models/023 Create Manifest file.mp4 30.0 MB
19 - Reference Getting Started with AWS/005 Setup CLI with Credentials.mp4 30.0 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/044 Advanced Plots in Seaborn.mp4 29.7 MB
07 - Docker for Machine Learning/003 Installation of Docker Desktop.mp4 29.5 MB
02 - Python for MLOps/026 Classes in Python.mp4 29.3 MB
13 - Monitoring and Debugging of ML System/001 Why Monitoring Machine Learning Models is Important.mp4 28.5 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/032 Matplotlib Basics.mp4 28.1 MB
05 - Packaging the ML Models/018 Perform Training and Predictions.mp4 27.9 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/013 Relational Operators & Aggregation Functions on Numpy Arrays.mp4 27.7 MB
19 - Reference Getting Started with AWS/011 Creation of S3 Bucket from CLI.mp4 27.7 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/006 Array Indexing and Slicing.mp4 27.3 MB
02 - Python for MLOps/009 Variables - Comments - Markdown Cells - Hands On.mp4 27.0 MB
03 - Git and Github Fundamentals for MLOps/003 Local Repo vs Remote Repo.mp4 26.8 MB
11 - Lnux Operating System for DevOps and Data Scientists/003 How to Launch EC2 Instances (Quick Refresh).mp4 26.7 MB
19 - Reference Getting Started with AWS/010 Creation of S3 Bucket from Console.mp4 26.5 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/035 Adjusting the Plots.mp4 26.5 MB
03 - Git and Github Fundamentals for MLOps/006 Concept of Working Directory - Staging Area - Commit.mp4 26.0 MB
03 - Git and Github Fundamentals for MLOps/004 Git Configurations.mp4 26.0 MB
02 - Python for MLOps/013 Python String - Builtin Functions - Hands On.mp4 25.0 MB
05 - Packaging the ML Models/014 Fixes on Python Scripts.mp4 25.0 MB
13 - Monitoring and Debugging of ML System/004 Challenge - Who Owns what.mp4 24.8 MB
14 - Continuous Monitoring with Prometheus/013 Monitor the Client Application using Prometheus.mp4 24.7 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/030 Data Cleaning.mp4 24.3 MB
05 - Packaging the ML Models/010 Data Preprocessing part 2.mp4 23.1 MB
12 - Working with CI CD Tool Jenkins/023 Perform Test of Pipeline.mp4 23.1 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/045 Which Plot to use.mp4 22.5 MB
07 - Docker for Machine Learning/007 Push the Docker Image to DockerHub.mp4 22.2 MB
02 - Python for MLOps/006 Jupyter Lab Quick Tour.mp4 21.8 MB
02 - Python for MLOps/015 Data Structures - Tuples.mp4 21.7 MB
12 - Working with CI CD Tool Jenkins/006 Create Dockerfile.mp4 21.3 MB
14 - Continuous Monitoring with Prometheus/011 Monitor the Infrastructure with Prometheus.mp4 20.3 MB
02 - Python for MLOps/017 Data Structures - Sets.mp4 19.9 MB
02 - Python for MLOps/021 Control Statements - Conditional Statements in Python.mp4 19.8 MB
09 - Build MLApps using Streamlit/001 Introduction to Streamit.mp4 18.7 MB
08 - Build MLApps using FastAPI/005 Data Validation with Pydantic.mp4 18.6 MB
05 - Packaging the ML Models/017 No module named prediction_model - fix.mp4 18.6 MB
07 - Docker for Machine Learning/001 Docker for Machine Learning.mp4 18.1 MB
05 - Packaging the ML Models/016 Add Python Path to Windows.mp4 18.1 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/026 Accessing Google Colab.mp4 18.0 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/016 Summary of Numpy Library Journey.mp4 17.5 MB
12 - Working with CI CD Tool Jenkins/014 Create your first First Jenkins Project.mp4 17.4 MB
05 - Packaging the ML Models/003 Model fit and generate Predictions.mp4 17.0 MB
18 - Post Productionizing ML Models/008 AB Testing.mp4 17.0 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/008 Copy Arrays.mp4 16.9 MB
12 - Working with CI CD Tool Jenkins/012 Introduction to Jenkins FreeStyle Projects and Pipeline Jobs.mp4 16.4 MB
02 - Python for MLOps/019 Reading the Input from Keyboard.mp4 16.3 MB
19 - Reference Getting Started with AWS/006 IAM Policy.mp4 15.7 MB
02 - Python for MLOps/016 Data Structures - Dictionary.mp4 15.0 MB
02 - Python for MLOps/020 String Formatting.mp4 14.8 MB
02 - Python for MLOps/003 Introduction to Python Programming.mp4 14.8 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/009 Mathematical Operation on Numpy Arrays.mp4 14.8 MB
02 - Python for MLOps/023 List comprehension.mp4 14.5 MB
05 - Packaging the ML Models/020 Testing the New Virtual Environments.mp4 14.4 MB
05 - Packaging the ML Models/015 Add Python Path to MacOS.mp4 14.3 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/040 Introduction to Seaborn.mp4 13.8 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/004 Creation of Array Object - np.array().mp4 13.7 MB
02 - Python for MLOps/025 Modules in Python.mp4 13.6 MB
15 - Deploy Applications with Docker Compose/001 Introduction to Docker Compose.mp4 13.2 MB
14 - Continuous Monitoring with Prometheus/005 Metric Types of Prometheus.mp4 13.1 MB
02 - Python for MLOps/004 Install Anaconda.mp4 13.1 MB
17 - Monitor the ML System with WhyLogs/005 Summary.mp4 12.3 MB
02 - Python for MLOps/018 Explicit and Implicit Casting in Python Programming.mp4 12.3 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/003 Import Numpy & Access help.mp4 12.1 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/002 Basics of numpy array object.mp4 11.9 MB
13 - Monitoring and Debugging of ML System/007 Operational Level Monitoring.mp4 11.7 MB
17 - Monitor the ML System with WhyLogs/002 Setting Up WhyLabs.mp4 11.6 MB
18 - Post Productionizing ML Models/001 Post-Productionalizing ML Models - What Next.mp4 11.5 MB
03 - Git and Github Fundamentals for MLOps/016 Summary.mp4 11.2 MB
14 - Continuous Monitoring with Prometheus/002 Use case on Continuous Monitoring.mp4 10.9 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/012 np.arange().mp4 10.9 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/039 Historgram Plot.mp4 10.9 MB
13 - Monitoring and Debugging of ML System/002 What is Monitoring of ML models & When to Update Model in Production.mp4 10.6 MB
18 - Post Productionizing ML Models/007 How to Mitigate Risk of Model Attacks.mp4 10.3 MB
05 - Packaging the ML Models/024 Create Version File.mp4 10.2 MB
14 - Continuous Monitoring with Prometheus/003 Introduction to Prometheus.mp4 10.2 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/005 Attributes of Numpy Array.mp4 9.1 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/025 Introduction to EDA.mp4 9.1 MB
06 - Mlflow - Manage ML experiments/013 Summary.mp4 8.6 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/010 Linear Algebra Functions in Numpy.mp4 8.5 MB
02 - Python for MLOps/029 Libraries in Python.mp4 8.5 MB
13 - Monitoring and Debugging of ML System/008 Tools and Best Practices of Machine Learning Model Monitoring.mp4 8.3 MB
12 - Working with CI CD Tool Jenkins/002 How do we Use Jenkins in MLOps.mp4 8.2 MB
10 - Build MLApps using Flask/001 What is Flask.mp4 8.2 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/017 Introduction to Pandas.mp4 8.1 MB
02 - Python for MLOps/028 Working with Python Scripts.mp4 7.4 MB
12 - Working with CI CD Tool Jenkins/007 Exposing the Application Port as per Dockerfile.mp4 7.4 MB
12 - Working with CI CD Tool Jenkins/018 Introduction to CI CT CD Pipeline.mp4 7.1 MB
12 - Working with CI CD Tool Jenkins/013 Exploration of Jenkins UI.mp4 7.1 MB
18 - Post Productionizing ML Models/003 Adversarial Attack.mp4 7.1 MB
18 - Post Productionizing ML Models/009 Future of MLOps.mp4 7.0 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/037 Scatter Plot.mp4 7.0 MB
19 - Reference Getting Started with AWS/015 Clean Up Activity.mp4 6.9 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/019 Mathematical Operation on Pandas Series.mp4 6.8 MB
02 - Python for MLOps/007 Variables in Python.mp4 6.1 MB
18 - Post Productionizing ML Models/002 Model Security.mp4 5.9 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/014 Boolean Masking.mp4 5.5 MB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/033 Types of Plot - Line plot.mp4 5.4 MB
02 - Python for MLOps/001 About the Section.mp4 5.1 MB
19 - Reference Getting Started with AWS/001 What do we cover in this section.mp4 4.2 MB
18 - Post Productionizing ML Models/005 Distributed Denial of Service Attack (DDOS).mp4 4.1 MB
14 - Continuous Monitoring with Prometheus/007 Introduction Grafana.mp4 4.0 MB
19 - Reference Getting Started with AWS/008 Delete the IAM User.mp4 3.9 MB
18 - Post Productionizing ML Models/006 Data Privacy Attack.mp4 3.8 MB
11 - Lnux Operating System for DevOps and Data Scientists/001 Agenda of this section.mp4 3.4 MB
18 - Post Productionizing ML Models/004 Data Poisoning Attack.mp4 2.1 MB
11 - Lnux Operating System for DevOps and Data Scientists/004 Basic Linux Commands of Linux.srt 138.9 KB
21 - Additional Learning on Topic of MLOps/004 Generative AI and Prompt Engineering Introduction.srt 98.0 KB
21 - Additional Learning on Topic of MLOps/005 Bonus Understanding Transformer Architecture.srt 71.0 KB
21 - Additional Learning on Topic of MLOps/001 MLOps with MLFlow in 1 Hour.srt 69.4 KB
17 - Monitor the ML System with WhyLogs/003 Whylogs - Drift Detection, Input, Output, Bias Monitoring.srt 64.7 KB
21 - Additional Learning on Topic of MLOps/002 Kubernetes 101 Part 1.srt 64.3 KB
21 - Additional Learning on Topic of MLOps/003 Kubernetes 101 Part 2.srt 47.9 KB
09 - Build MLApps using Streamlit/003 Building the ML Model with Streamlit.srt 47.9 KB
05 - Packaging the ML Models/002 Typical Experimentation with Dataset.srt 37.9 KB
07 - Docker for Machine Learning/002 Introduction to Docker.srt 34.2 KB
05 - Packaging the ML Models/009 Data Preprocessing part 1.srt 33.4 KB
05 - Packaging the ML Models/004 Challenges in Working inside the Jupyter Notebook.srt 31.6 KB
08 - Build MLApps using FastAPI/004 Crash course on FastAPI.srt 31.5 KB
04 - Crash Course on YAML/001 YAML Crash Course.srt 30.0 KB
05 - Packaging the ML Models/007 Create Config Module.srt 29.7 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/024 Advanced Functions in Pandas DataFrame.srt 29.6 KB
10 - Build MLApps using Flask/002 Hands On Learning of Flask Library.srt 28.9 KB
15 - Deploy Applications with Docker Compose/002 Hands On - Docker Compose with Flask Application.srt 28.8 KB
06 - Mlflow - Manage ML experiments/008 MLFlow Project.srt 28.4 KB
11 - Lnux Operating System for DevOps and Data Scientists/002 Linux Features & Bash.srt 27.0 KB
12 - Working with CI CD Tool Jenkins/011 Configure Github Repo - Webhook - Jenkins Credentials.srt 26.6 KB
06 - Mlflow - Manage ML experiments/006 Machine Learning Experiement on MLFlow.srt 26.4 KB
12 - Working with CI CD Tool Jenkins/004 Deploy as API with FASTAPI.srt 26.2 KB
09 - Build MLApps using Streamlit/002 Hands On Working with Streamlit.srt 26.0 KB
06 - Mlflow - Manage ML experiments/004 Basic Mlflow tutorial.srt 25.4 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/015 Broadcasting on Numpy Arrays.srt 25.3 KB
05 - Packaging the ML Models/005 Understanding the Modular Programming.srt 24.7 KB
06 - Mlflow - Manage ML experiments/012 Register the Model & Serve the Model.srt 24.6 KB
07 - Docker for Machine Learning/004 Working with Docker.srt 24.6 KB
06 - Mlflow - Manage ML experiments/011 Log Model Metrics in MySql.srt 23.6 KB
05 - Packaging the ML Models/006 Creating Folder Hierarchy for ML Project.srt 23.2 KB
14 - Continuous Monitoring with Prometheus/016 Create Visualization with Grafana.srt 23.0 KB
05 - Packaging the ML Models/026 Packagiing the ML Model & testing.srt 22.5 KB
06 - Mlflow - Manage ML experiments/009 MLFlow Models.srt 21.9 KB
12 - Working with CI CD Tool Jenkins/019 Create CI CT CD Pipeline - Github Dockerhub.srt 21.1 KB
15 - Deploy Applications with Docker Compose/003 Hands On - Docker Compose Prometheus Grafana.srt 21.1 KB
12 - Working with CI CD Tool Jenkins/015 Test Github Webhook with Jenkins.srt 20.9 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/028 Preliminary Analysis on DataFrame.srt 20.5 KB
12 - Working with CI CD Tool Jenkins/001 Introduction to Jenkins.srt 20.2 KB
14 - Continuous Monitoring with Prometheus/006 Installation of Prometheus.srt 20.2 KB
16 - Continuous Monitoring of Machine Learning Application/002 Hands On Monitoring of ML Application using Prometheus.srt 20.1 KB
02 - Python for MLOps/002 Python Quiz.html 19.6 KB
05 - Packaging the ML Models/021 Create Python tests.srt 19.0 KB
19 - Reference Getting Started with AWS/009 S3 Bucket and Storage Classes.srt 18.5 KB
14 - Continuous Monitoring with Prometheus/017 Trigger Alerts with Grafana.srt 18.0 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/020 Dataframes in Pandas.srt 17.9 KB
12 - Working with CI CD Tool Jenkins/017 Setup Email Notification with Gmail.srt 17.4 KB
03 - Git and Github Fundamentals for MLOps/008 Git Branch.srt 17.0 KB
13 - Monitoring and Debugging of ML System/005 Functional Level Monitoring.srt 17.0 KB
08 - Build MLApps using FastAPI/002 How REST API Works.srt 16.9 KB
10 - Build MLApps using Flask/003 Build ML Model App with Flask.srt 16.8 KB
02 - Python for MLOps/022 Control Statements - Looping Statements.srt 16.7 KB
17 - Monitor the ML System with WhyLogs/001 Introduction to ML Monitoring.srt 16.6 KB
03 - Git and Github Fundamentals for MLOps/013 Working with Remote Repositories.srt 16.5 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/042 Univariate & Bivariate Plots - Continuous Data.srt 16.3 KB
05 - Packaging the ML Models/011 sklearn pipeline.srt 16.3 KB
02 - Python for MLOps/012 Collection - Strings.srt 15.7 KB
12 - Working with CI CD Tool Jenkins/009 Installation of Jenkins on AWS EC2 Instances.srt 15.7 KB
06 - Mlflow - Manage ML experiments/007 Create ML Model for Loan Prediction.srt 15.5 KB
14 - Continuous Monitoring with Prometheus/004 Architecture of Prometheus.srt 15.5 KB
06 - Mlflow - Manage ML experiments/003 Logging Functions of Mlflow Tracking.srt 15.4 KB
12 - Working with CI CD Tool Jenkins/008 Test Locally using Docker Containers.srt 15.3 KB
07 - Docker for Machine Learning/008 Dockerize the ML Model.srt 15.2 KB
13 - Monitoring and Debugging of ML System/003 Why Monitoring Machine Learning Models is Difficult.srt 15.2 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/007 Array Creation Functions.srt 15.1 KB
07 - Docker for Machine Learning/006 Working with Dockerfile.srt 14.9 KB
06 - Mlflow - Manage ML experiments/001 Introduction to Mlflow.srt 14.8 KB
03 - Git and Github Fundamentals for MLOps/007 Git Workflow - Local Repo.srt 14.7 KB
12 - Working with CI CD Tool Jenkins/016 Installation of Docker Plugin & System Readiness.srt 14.6 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/041 Exploring the data.srt 14.6 KB
12 - Working with CI CD Tool Jenkins/005 Test FastAPI App.srt 14.5 KB
02 - Python for MLOps/009 Variables - Comments - Markdown Cells - Hands On.srt 14.5 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/023 Other Functions on Pandas DataFrame.srt 14.5 KB
17 - Monitor the ML System with WhyLogs/004 WhyLogs - Constraints and Drift Reports.srt 14.3 KB
14 - Continuous Monitoring with Prometheus/014 Monitor the FastAPI Application using Prometheus.srt 14.1 KB
05 - Packaging the ML Models/012 Training Pipeline.srt 14.0 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/038 Scatter Plot hands on.srt 14.0 KB
14 - Continuous Monitoring with Prometheus/012 Monitor the Linux Server with Node Exporter.srt 13.8 KB
02 - Python for MLOps/024 Functions.srt 13.7 KB
03 - Git and Github Fundamentals for MLOps/015 3 way merge.srt 13.7 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/030 Data Cleaning.srt 13.6 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/032 Matplotlib Basics.srt 13.5 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/011 Shape Modification of Arrays.srt 13.5 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/043 Plot - Categorical Data.srt 13.4 KB
13 - Monitoring and Debugging of ML System/006 Model Drift.srt 13.4 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/022 Combining the DataFrames.srt 13.2 KB
02 - Python for MLOps/011 Operators in Python Programming Language.srt 13.1 KB
02 - Python for MLOps/010 Python Literals - Hands On.srt 13.0 KB
03 - Git and Github Fundamentals for MLOps/001 Introduction to Version Control Systems.srt 13.0 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/034 Line Plots Hands On.srt 12.9 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/006 Array Indexing and Slicing.srt 12.8 KB
08 - Build MLApps using FastAPI/006 Deploying the Machine Learning Model with FastAPI.srt 12.6 KB
07 - Docker for Machine Learning/005 Running the Docker Container.srt 12.6 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/035 Adjusting the Plots.srt 12.5 KB
05 - Packaging the ML Models/025 Create setup.py.srt 12.3 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/021 Working with Data in Pandas DataFrame.srt 12.3 KB
19 - Reference Getting Started with AWS/014 Launch EC2 instance & SSH into EC2 Instances.srt 12.2 KB
19 - Reference Getting Started with AWS/003 Setting up MFA on Root Account.srt 11.9 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/018 Working with Pandas Series.srt 11.8 KB
12 - Working with CI CD Tool Jenkins/003 Prepare and Package ML Model.srt 11.8 KB
05 - Packaging the ML Models/013 Prediction Pipeline.srt 11.7 KB
03 - Git and Github Fundamentals for MLOps/011 Checking Out Commits.srt 11.3 KB
03 - Git and Github Fundamentals for MLOps/009 Switching the Branches.srt 11.2 KB
06 - Mlflow - Manage ML experiments/010 Setting Up MySql Database Locally.srt 11.2 KB
03 - Git and Github Fundamentals for MLOps/010 Merging.srt 11.1 KB
12 - Working with CI CD Tool Jenkins/020 Create CI CT CD Pipeline - Training.srt 11.1 KB
14 - Continuous Monitoring with Prometheus/015 Monitor All EndPoints using Prometheus.srt 10.9 KB
19 - Reference Getting Started with AWS/010 Creation of S3 Bucket from Console.srt 10.9 KB
07 - Docker for Machine Learning/009 Packaging the training code in Docker Environment & Summary.srt 10.9 KB
14 - Continuous Monitoring with Prometheus/001 Introduction to Continuous Monitoring.srt 10.9 KB
02 - Python for MLOps/014 Data Structures - List.srt 10.8 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/036 Plot Adjustment Hands On.srt 10.8 KB
06 - Mlflow - Manage ML experiments/005 Exploration of mlflow.srt 10.7 KB
05 - Packaging the ML Models/008 Data Handling Module.srt 10.5 KB
14 - Continuous Monitoring with Prometheus/010 Exploring the Basic Querying Prometheus.srt 10.5 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/027 Loading the Large Dataset for Working.srt 10.5 KB
03 - Git and Github Fundamentals for MLOps/005 Getting Started with Local Repo.srt 10.3 KB
02 - Python for MLOps/027 File Handling in Python.srt 10.0 KB
14 - Continuous Monitoring with Prometheus/009 Prometheus Configuration file.srt 9.8 KB
03 - Git and Github Fundamentals for MLOps/014 Cloning and Delete Branches.srt 9.8 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/029 Null values in the Dataframe.srt 9.5 KB
19 - Reference Getting Started with AWS/004 Create IAM Account and Account Alias.srt 9.5 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/044 Advanced Plots in Seaborn.srt 9.5 KB
05 - Packaging the ML Models/022 Running Pytest.srt 9.4 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/001 Introduction to Numpy Library.srt 9.4 KB
01 - Introduction to Complete MLOps Bootcamp/002 What and Why MLOps.html 9.3 KB
01 - Introduction to Complete MLOps Bootcamp/004 Stages of MLOps.html 9.2 KB
01 - Introduction to Complete MLOps Bootcamp/003 The Stages of MLOps.srt 9.1 KB
03 - Git and Github Fundamentals for MLOps/006 Concept of Working Directory - Staging Area - Commit.srt 9.1 KB
08 - Build MLApps using FastAPI/005 Data Validation with Pydantic.srt 9.0 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/013 Relational Operators & Aggregation Functions on Numpy Arrays.srt 9.0 KB
02 - Python for MLOps/026 Classes in Python.srt 8.9 KB
11 - Lnux Operating System for DevOps and Data Scientists/003 How to Launch EC2 Instances (Quick Refresh).srt 8.8 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/031 Introduction to Data Visualization.srt 8.8 KB
02 - Python for MLOps/008 Variables in Python.html 8.7 KB
08 - Build MLApps using FastAPI/001 What is API, REST and REST API.srt 8.6 KB
19 - Reference Getting Started with AWS/012 Version Enablement in S3.srt 8.5 KB
12 - Working with CI CD Tool Jenkins/024 Summary.srt 8.3 KB
06 - Mlflow - Manage ML experiments/002 Getting System Ready with mlflow.srt 8.3 KB
03 - Git and Github Fundamentals for MLOps/002 Getting Started with git.srt 8.3 KB
02 - Python for MLOps/006 Jupyter Lab Quick Tour.srt 8.0 KB
12 - Working with CI CD Tool Jenkins/022 Create CI CT CD Pipeline - Deployment.srt 7.9 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/039 Historgram Plot.srt 7.9 KB
12 - Working with CI CD Tool Jenkins/006 Create Dockerfile.srt 7.9 KB
03 - Git and Github Fundamentals for MLOps/004 Git Configurations.srt 7.9 KB
02 - Python for MLOps/021 Control Statements - Conditional Statements in Python.srt 7.9 KB
05 - Packaging the ML Models/019 Requirements txt file.srt 7.8 KB
05 - Packaging the ML Models/001 Introduction to Packaging the ML Models.srt 7.8 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/026 Accessing Google Colab.srt 7.5 KB
12 - Working with CI CD Tool Jenkins/021 Create CI CT CD Pipeline - Testing.srt 7.5 KB
12 - Working with CI CD Tool Jenkins/014 Create your first First Jenkins Project.srt 7.4 KB
12 - Working with CI CD Tool Jenkins/010 Installation of Docker in EC2 Instance.srt 7.4 KB
05 - Packaging the ML Models/020 Testing the New Virtual Environments.srt 7.3 KB
05 - Packaging the ML Models/027 Summary.srt 7.3 KB
05 - Packaging the ML Models/023 Create Manifest file.srt 7.2 KB
03 - Git and Github Fundamentals for MLOps/012 Git Hosting Services.srt 7.2 KB
02 - Python for MLOps/003 Introduction to Python Programming.srt 7.2 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/045 Which Plot to use.srt 7.0 KB
14 - Continuous Monitoring with Prometheus/008 Installation of Grafana.srt 6.9 KB
16 - Continuous Monitoring of Machine Learning Application/001 Architecture of ML Application Monitoring.srt 6.8 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/003 Import Numpy & Access help.srt 6.8 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/008 Copy Arrays.srt 6.7 KB
19 - Reference Getting Started with AWS/005 Setup CLI with Credentials.srt 6.7 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/004 Creation of Array Object - np.array().srt 6.6 KB
13 - Monitoring and Debugging of ML System/004 Challenge - Who Owns what.srt 6.5 KB
02 - Python for MLOps/020 String Formatting.srt 6.4 KB
19 - Reference Getting Started with AWS/011 Creation of S3 Bucket from CLI.srt 6.4 KB
02 - Python for MLOps/018 Explicit and Implicit Casting in Python Programming.srt 6.4 KB
02 - Python for MLOps/025 Modules in Python.srt 6.3 KB
08 - Build MLApps using FastAPI/003 What is FastAPI.srt 6.3 KB
12 - Working with CI CD Tool Jenkins/002 How do we Use Jenkins in MLOps.srt 6.3 KB
18 - Post Productionizing ML Models/001 Post-Productionalizing ML Models - What Next.srt 6.3 KB
02 - Python for MLOps/016 Data Structures - Dictionary.srt 6.3 KB
19 - Reference Getting Started with AWS/002 Create AWS Account.srt 6.3 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/009 Mathematical Operation on Numpy Arrays.srt 6.2 KB
03 - Git and Github Fundamentals for MLOps/003 Local Repo vs Remote Repo.srt 6.0 KB
05 - Packaging the ML Models/003 Model fit and generate Predictions.srt 5.9 KB
14 - Continuous Monitoring with Prometheus/003 Introduction to Prometheus.srt 5.7 KB
14 - Continuous Monitoring with Prometheus/013 Monitor the Client Application using Prometheus.srt 5.7 KB
02 - Python for MLOps/023 List comprehension.srt 5.6 KB
07 - Docker for Machine Learning/001 Docker for Machine Learning.srt 5.5 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/002 Basics of numpy array object.srt 5.5 KB
12 - Working with CI CD Tool Jenkins/012 Introduction to Jenkins FreeStyle Projects and Pipeline Jobs.srt 5.5 KB
02 - Python for MLOps/013 Python String - Builtin Functions - Hands On.srt 5.5 KB
05 - Packaging the ML Models/014 Fixes on Python Scripts.srt 5.5 KB
19 - Reference Getting Started with AWS/013 Introduction EC2 instances.srt 5.4 KB
02 - Python for MLOps/005 Hello World - Python.srt 5.4 KB
02 - Python for MLOps/015 Data Structures - Tuples.srt 5.4 KB
14 - Continuous Monitoring with Prometheus/005 Metric Types of Prometheus.srt 5.3 KB
13 - Monitoring and Debugging of ML System/001 Why Monitoring Machine Learning Models is Important.srt 5.3 KB
15 - Deploy Applications with Docker Compose/001 Introduction to Docker Compose.srt 5.2 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/012 np.arange().srt 5.2 KB
09 - Build MLApps using Streamlit/001 Introduction to Streamit.srt 5.2 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/005 Attributes of Numpy Array.srt 5.1 KB
18 - Post Productionizing ML Models/008 AB Testing.srt 5.1 KB
12 - Working with CI CD Tool Jenkins/013 Exploration of Jenkins UI.srt 5.1 KB
02 - Python for MLOps/007 Variables in Python.srt 5.0 KB
02 - Python for MLOps/017 Data Structures - Sets.srt 4.9 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/025 Introduction to EDA.srt 4.9 KB
05 - Packaging the ML Models/016 Add Python Path to Windows.srt 4.9 KB
02 - Python for MLOps/019 Reading the Input from Keyboard.srt 4.9 KB
01 - Introduction to Complete MLOps Bootcamp/001 What and Why MLOps.srt 4.9 KB
05 - Packaging the ML Models/018 Perform Training and Predictions.srt 4.7 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/037 Scatter Plot.srt 4.7 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/010 Linear Algebra Functions in Numpy.srt 4.7 KB
05 - Packaging the ML Models/015 Add Python Path to MacOS.srt 4.7 KB
14 - Continuous Monitoring with Prometheus/002 Use case on Continuous Monitoring.srt 4.6 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/040 Introduction to Seaborn.srt 4.6 KB
05 - Packaging the ML Models/010 Data Preprocessing part 2.srt 4.5 KB
05 - Packaging the ML Models/024 Create Version File.srt 4.4 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/033 Types of Plot - Line plot.srt 4.3 KB
07 - Docker for Machine Learning/007 Push the Docker Image to DockerHub.srt 4.3 KB
13 - Monitoring and Debugging of ML System/007 Operational Level Monitoring.srt 4.3 KB
18 - Post Productionizing ML Models/009 Future of MLOps.srt 4.2 KB
13 - Monitoring and Debugging of ML System/002 What is Monitoring of ML models & When to Update Model in Production.srt 4.0 KB
12 - Working with CI CD Tool Jenkins/023 Perform Test of Pipeline.srt 4.0 KB
13 - Monitoring and Debugging of ML System/008 Tools and Best Practices of Machine Learning Model Monitoring.srt 4.0 KB
18 - Post Productionizing ML Models/003 Adversarial Attack.srt 4.0 KB
18 - Post Productionizing ML Models/007 How to Mitigate Risk of Model Attacks.srt 3.9 KB
05 - Packaging the ML Models/017 No module named prediction_model - fix.srt 3.9 KB
17 - Monitor the ML System with WhyLogs/005 Summary.srt 3.8 KB
03 - Git and Github Fundamentals for MLOps/016 Summary.srt 3.8 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/019 Mathematical Operation on Pandas Series.srt 3.7 KB
14 - Continuous Monitoring with Prometheus/011 Monitor the Infrastructure with Prometheus.srt 3.5 KB
02 - Python for MLOps/029 Libraries in Python.srt 3.4 KB
10 - Build MLApps using Flask/001 What is Flask.srt 3.4 KB
02 - Python for MLOps/028 Working with Python Scripts.srt 3.4 KB
02 - Python for MLOps/004 Install Anaconda.srt 3.3 KB
12 - Working with CI CD Tool Jenkins/018 Introduction to CI CT CD Pipeline.srt 2.9 KB
18 - Post Productionizing ML Models/002 Model Security.srt 2.9 KB
20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/014 Boolean Masking.srt 2.9 KB
19 - Reference Getting Started with AWS/001 What do we cover in this section.srt 2.8 KB
06 - Mlflow - Manage ML experiments/013 Summary.srt 2.8 KB
14 - Continuous Monitoring with Prometheus/007 Introduction Grafana.srt 2.7 KB
11 - Lnux Operating System for DevOps and Data Scientists/001 Agenda of this section.srt 2.5 KB
17 - Monitor the ML System with WhyLogs/002 Setting Up WhyLabs.srt 2.4 KB
02 - Python for MLOps/001 About the Section.srt 2.3 KB
18 - Post Productionizing ML Models/006 Data Privacy Attack.srt 2.1 KB
12 - Working with CI CD Tool Jenkins/007 Exposing the Application Port as per Dockerfile.srt 2.1 KB
19 - Reference Getting Started with AWS/008 Delete the IAM User.srt 1.7 KB
19 - Reference Getting Started with AWS/015 Clean Up Activity.srt 1.3 KB
18 - Post Productionizing ML Models/004 Data Poisoning Attack.srt 1.3 KB
18 - Post Productionizing ML Models/005 Distributed Denial of Service Attack (DDOS).srt 1.1 KB
01 - Introduction to Complete MLOps Bootcamp/external-links.txt 167 bytes
01 - Introduction to Complete MLOps Bootcamp/005 Source code for this course.html 114 bytes
01 - Introduction to Complete MLOps Bootcamp/006 Slide Download Link.html 93 bytes
01 - Introduction to Complete MLOps Bootcamp/005 Github-Link.url 85 bytes
01 - Introduction to Complete MLOps Bootcamp/006 Slide-Download-Link.url 80 bytes
07 - Docker for Machine Learning/003 Installation of Docker Desktop.srt 0 bytes

Udemy - MLOps Bootcamp Mastering AI Operations for Success - AIOps (7.2024)

File List

Download Torrent

Related Resources

Copyright Infringement