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

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

磁力链接/BT种子简介

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文件大小： 13.84G
已经下载：244次
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收录时间：2025-07-19
最近下载：2025-09-17

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文件列表

  • 11 - Lnux Operating System for DevOps and Data Scientists/004 Basic Linux Commands of Linux.mp4 594.3 MB
  • 21 - Additional Learning on Topic of MLOps/003 Kubernetes 101 Part 2.mp4 448.8 MB
  • 21 - Additional Learning on Topic of MLOps/001 MLOps with MLFlow in 1 Hour.mp4 435.5 MB
  • 17 - Monitor the ML System with WhyLogs/003 Whylogs - Drift Detection, Input, Output, Bias Monitoring.mp4 403.4 MB
  • 21 - Additional Learning on Topic of MLOps/005 Bonus Understanding Transformer Architecture.mp4 402.3 MB
  • 09 - Build MLApps using Streamlit/003 Building the ML Model with Streamlit.mp4 346.0 MB
  • 21 - Additional Learning on Topic of MLOps/004 Generative AI and Prompt Engineering Introduction.mp4 208.0 MB
  • 05 - Packaging the ML Models/002 Typical Experimentation with Dataset.mp4 185.4 MB
  • 05 - Packaging the ML Models/009 Data Preprocessing part 1.mp4 175.6 MB
  • 05 - Packaging the ML Models/007 Create Config Module.mp4 174.2 MB
  • 21 - Additional Learning on Topic of MLOps/002 Kubernetes 101 Part 1.mp4 167.0 MB
  • 06 - Mlflow - Manage ML experiments/008 MLFlow Project.mp4 159.5 MB
  • 15 - Deploy Applications with Docker Compose/002 Hands On - Docker Compose with Flask Application.mp4 156.0 MB
  • 12 - Working with CI CD Tool Jenkins/004 Deploy as API with FASTAPI.mp4 148.3 MB
  • 06 - Mlflow - Manage ML experiments/006 Machine Learning Experiement on MLFlow.mp4 147.0 MB
  • 07 - Docker for Machine Learning/002 Introduction to Docker.mp4 144.3 MB
  • 01 - Introduction to Complete MLOps Bootcamp/003 The Stages of MLOps.mp4 142.9 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/024 Advanced Functions in Pandas DataFrame.mp4 142.9 MB
  • 15 - Deploy Applications with Docker Compose/003 Hands On - Docker Compose Prometheus Grafana.mp4 140.3 MB
  • 12 - Working with CI CD Tool Jenkins/011 Configure Github Repo - Webhook - Jenkins Credentials.mp4 140.1 MB
  • 05 - Packaging the ML Models/026 Packagiing the ML Model & testing.mp4 138.9 MB
  • 11 - Lnux Operating System for DevOps and Data Scientists/002 Linux Features & Bash.mp4 138.8 MB
  • 12 - Working with CI CD Tool Jenkins/019 Create CI CT CD Pipeline - Github Dockerhub.mp4 138.2 MB
  • 07 - Docker for Machine Learning/004 Working with Docker.mp4 136.7 MB
  • 06 - Mlflow - Manage ML experiments/004 Basic Mlflow tutorial.mp4 135.7 MB
  • 16 - Continuous Monitoring of Machine Learning Application/002 Hands On Monitoring of ML Application using Prometheus.mp4 132.2 MB
  • 06 - Mlflow - Manage ML experiments/011 Log Model Metrics in MySql.mp4 130.7 MB
  • 10 - Build MLApps using Flask/002 Hands On Learning of Flask Library.mp4 129.9 MB
  • 08 - Build MLApps using FastAPI/004 Crash course on FastAPI.mp4 128.2 MB
  • 05 - Packaging the ML Models/004 Challenges in Working inside the Jupyter Notebook.mp4 121.2 MB
  • 14 - Continuous Monitoring with Prometheus/006 Installation of Prometheus.mp4 119.4 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/015 Broadcasting on Numpy Arrays.mp4 118.5 MB
  • 09 - Build MLApps using Streamlit/002 Hands On Working with Streamlit.mp4 112.2 MB
  • 05 - Packaging the ML Models/005 Understanding the Modular Programming.mp4 111.7 MB
  • 14 - Continuous Monitoring with Prometheus/014 Monitor the FastAPI Application using Prometheus.mp4 109.8 MB
  • 10 - Build MLApps using Flask/003 Build ML Model App with Flask.mp4 109.2 MB
  • 06 - Mlflow - Manage ML experiments/009 MLFlow Models.mp4 107.7 MB
  • 12 - Working with CI CD Tool Jenkins/017 Setup Email Notification with Gmail.mp4 106.0 MB
  • 05 - Packaging the ML Models/006 Creating Folder Hierarchy for ML Project.mp4 105.6 MB
  • 12 - Working with CI CD Tool Jenkins/008 Test Locally using Docker Containers.mp4 105.4 MB
  • 14 - Continuous Monitoring with Prometheus/017 Trigger Alerts with Grafana.mp4 105.2 MB
  • 12 - Working with CI CD Tool Jenkins/015 Test Github Webhook with Jenkins.mp4 105.1 MB
  • 05 - Packaging the ML Models/011 sklearn pipeline.mp4 104.1 MB
  • 12 - Working with CI CD Tool Jenkins/005 Test FastAPI App.mp4 101.5 MB
  • 07 - Docker for Machine Learning/008 Dockerize the ML Model.mp4 100.1 MB
  • 03 - Git and Github Fundamentals for MLOps/008 Git Branch.mp4 98.4 MB
  • 04 - Crash Course on YAML/001 YAML Crash Course.mp4 96.3 MB
  • 06 - Mlflow - Manage ML experiments/007 Create ML Model for Loan Prediction.mp4 95.8 MB
  • 14 - Continuous Monitoring with Prometheus/012 Monitor the Linux Server with Node Exporter.mp4 94.6 MB
  • 07 - Docker for Machine Learning/006 Working with Dockerfile.mp4 93.9 MB
  • 12 - Working with CI CD Tool Jenkins/001 Introduction to Jenkins.mp4 91.6 MB
  • 05 - Packaging the ML Models/025 Create setup.py.mp4 88.6 MB
  • 12 - Working with CI CD Tool Jenkins/009 Installation of Jenkins on AWS EC2 Instances.mp4 88.3 MB
  • 01 - Introduction to Complete MLOps Bootcamp/001 What and Why MLOps.mp4 86.9 MB
  • 06 - Mlflow - Manage ML experiments/012 Register the Model & Serve the Model.mp4 85.6 MB
  • 07 - Docker for Machine Learning/005 Running the Docker Container.mp4 85.4 MB
  • 05 - Packaging the ML Models/012 Training Pipeline.mp4 83.9 MB
  • 06 - Mlflow - Manage ML experiments/003 Logging Functions of Mlflow Tracking.mp4 81.4 MB
  • 14 - Continuous Monitoring with Prometheus/009 Prometheus Configuration file.mp4 78.3 MB
  • 08 - Build MLApps using FastAPI/002 How REST API Works.mp4 76.4 MB
  • 03 - Git and Github Fundamentals for MLOps/010 Merging.mp4 75.5 MB
  • 08 - Build MLApps using FastAPI/006 Deploying the Machine Learning Model with FastAPI.mp4 74.3 MB
  • 03 - Git and Github Fundamentals for MLOps/015 3 way merge.mp4 74.2 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/042 Univariate & Bivariate Plots - Continuous Data.mp4 73.0 MB
  • 07 - Docker for Machine Learning/009 Packaging the training code in Docker Environment & Summary.mp4 71.9 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/022 Combining the DataFrames.mp4 70.2 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/028 Preliminary Analysis on DataFrame.mp4 70.0 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/041 Exploring the data.mp4 69.6 MB
  • 12 - Working with CI CD Tool Jenkins/016 Installation of Docker Plugin & System Readiness.mp4 67.9 MB
  • 17 - Monitor the ML System with WhyLogs/004 WhyLogs - Constraints and Drift Reports.mp4 67.8 MB
  • 14 - Continuous Monitoring with Prometheus/004 Architecture of Prometheus.mp4 66.6 MB
  • 14 - Continuous Monitoring with Prometheus/010 Exploring the Basic Querying Prometheus.mp4 66.3 MB
  • 03 - Git and Github Fundamentals for MLOps/007 Git Workflow - Local Repo.mp4 65.7 MB
  • 05 - Packaging the ML Models/008 Data Handling Module.mp4 64.4 MB
  • 05 - Packaging the ML Models/022 Running Pytest.mp4 62.9 MB
  • 19 - Reference Getting Started with AWS/014 Launch EC2 instance & SSH into EC2 Instances.mp4 62.8 MB
  • 02 - Python for MLOps/012 Collection - Strings.mp4 61.5 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/023 Other Functions on Pandas DataFrame.mp4 60.9 MB
  • 03 - Git and Github Fundamentals for MLOps/002 Getting Started with git.mp4 60.0 MB
  • 06 - Mlflow - Manage ML experiments/001 Introduction to Mlflow.mp4 59.8 MB
  • 14 - Continuous Monitoring with Prometheus/015 Monitor All EndPoints using Prometheus.mp4 59.6 MB
  • 19 - Reference Getting Started with AWS/007 IAM Policy generator & attachment.mp4 58.8 MB
  • 03 - Git and Github Fundamentals for MLOps/014 Cloning and Delete Branches.mp4 58.5 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/021 Working with Data in Pandas DataFrame.mp4 58.4 MB
  • 03 - Git and Github Fundamentals for MLOps/009 Switching the Branches.mp4 57.7 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/031 Introduction to Data Visualization.mp4 57.5 MB
  • 03 - Git and Github Fundamentals for MLOps/013 Working with Remote Repositories.mp4 57.1 MB
  • 12 - Working with CI CD Tool Jenkins/020 Create CI CT CD Pipeline - Training.mp4 56.9 MB
  • 03 - Git and Github Fundamentals for MLOps/011 Checking Out Commits.mp4 56.8 MB
  • 02 - Python for MLOps/011 Operators in Python Programming Language.mp4 55.0 MB
  • 12 - Working with CI CD Tool Jenkins/003 Prepare and Package ML Model.mp4 53.6 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/029 Null values in the Dataframe.mp4 53.1 MB
  • 03 - Git and Github Fundamentals for MLOps/005 Getting Started with Local Repo.mp4 52.9 MB
  • 19 - Reference Getting Started with AWS/004 Create IAM Account and Account Alias.mp4 52.4 MB
  • 06 - Mlflow - Manage ML experiments/005 Exploration of mlflow.mp4 52.3 MB
  • 13 - Monitoring and Debugging of ML System/005 Functional Level Monitoring.mp4 51.8 MB
  • 14 - Continuous Monitoring with Prometheus/001 Introduction to Continuous Monitoring.mp4 50.3 MB
  • 08 - Build MLApps using FastAPI/001 What is API, REST and REST API.mp4 50.1 MB
  • 05 - Packaging the ML Models/001 Introduction to Packaging the ML Models.mp4 49.7 MB
  • 17 - Monitor the ML System with WhyLogs/001 Introduction to ML Monitoring.mp4 49.0 MB
  • 02 - Python for MLOps/010 Python Literals - Hands On.mp4 48.0 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/027 Loading the Large Dataset for Working.mp4 47.6 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/007 Array Creation Functions.mp4 47.3 MB
  • 14 - Continuous Monitoring with Prometheus/016 Create Visualization with Grafana.mp4 46.4 MB
  • 05 - Packaging the ML Models/013 Prediction Pipeline.mp4 46.2 MB
  • 19 - Reference Getting Started with AWS/009 S3 Bucket and Storage Classes.mp4 46.0 MB
  • 12 - Working with CI CD Tool Jenkins/022 Create CI CT CD Pipeline - Deployment.mp4 45.6 MB
  • 12 - Working with CI CD Tool Jenkins/021 Create CI CT CD Pipeline - Testing.mp4 45.3 MB
  • 13 - Monitoring and Debugging of ML System/003 Why Monitoring Machine Learning Models is Difficult.mp4 45.3 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/038 Scatter Plot hands on.mp4 45.2 MB
  • 02 - Python for MLOps/027 File Handling in Python.mp4 45.1 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/018 Working with Pandas Series.mp4 45.1 MB
  • 05 - Packaging the ML Models/019 Requirements txt file.mp4 44.7 MB
  • 05 - Packaging the ML Models/021 Create Python tests.mp4 44.5 MB
  • 06 - Mlflow - Manage ML experiments/010 Setting Up MySql Database Locally.mp4 43.6 MB
  • 02 - Python for MLOps/024 Functions.mp4 42.9 MB
  • 05 - Packaging the ML Models/027 Summary.mp4 42.7 MB
  • 12 - Working with CI CD Tool Jenkins/010 Installation of Docker in EC2 Instance.mp4 42.6 MB
  • 19 - Reference Getting Started with AWS/002 Create AWS Account.mp4 40.8 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/011 Shape Modification of Arrays.mp4 40.8 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/043 Plot - Categorical Data.mp4 40.7 MB
  • 14 - Continuous Monitoring with Prometheus/008 Installation of Grafana.mp4 39.8 MB
  • 02 - Python for MLOps/014 Data Structures - List.mp4 38.5 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/034 Line Plots Hands On.mp4 38.4 MB
  • 03 - Git and Github Fundamentals for MLOps/001 Introduction to Version Control Systems.mp4 36.4 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/001 Introduction to Numpy Library.mp4 36.3 MB
  • 02 - Python for MLOps/022 Control Statements - Looping Statements.mp4 36.2 MB
  • 06 - Mlflow - Manage ML experiments/002 Getting System Ready with mlflow.mp4 36.1 MB
  • 03 - Git and Github Fundamentals for MLOps/012 Git Hosting Services.mp4 35.7 MB
  • 19 - Reference Getting Started with AWS/012 Version Enablement in S3.mp4 35.3 MB
  • 13 - Monitoring and Debugging of ML System/006 Model Drift.mp4 35.3 MB
  • 08 - Build MLApps using FastAPI/003 What is FastAPI.mp4 33.7 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/036 Plot Adjustment Hands On.mp4 33.6 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/020 Dataframes in Pandas.mp4 33.6 MB
  • 19 - Reference Getting Started with AWS/013 Introduction EC2 instances.mp4 33.5 MB
  • 16 - Continuous Monitoring of Machine Learning Application/001 Architecture of ML Application Monitoring.mp4 33.0 MB
  • 02 - Python for MLOps/005 Hello World - Python.mp4 32.6 MB
  • 12 - Working with CI CD Tool Jenkins/024 Summary.mp4 32.5 MB
  • 19 - Reference Getting Started with AWS/003 Setting up MFA on Root Account.mp4 32.2 MB
  • 05 - Packaging the ML Models/023 Create Manifest file.mp4 31.5 MB
  • 19 - Reference Getting Started with AWS/005 Setup CLI with Credentials.mp4 31.4 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/044 Advanced Plots in Seaborn.mp4 31.1 MB
  • 07 - Docker for Machine Learning/003 Installation of Docker Desktop.mp4 31.0 MB
  • 02 - Python for MLOps/026 Classes in Python.mp4 30.7 MB
  • 13 - Monitoring and Debugging of ML System/001 Why Monitoring Machine Learning Models is Important.mp4 29.9 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/032 Matplotlib Basics.mp4 29.5 MB
  • 05 - Packaging the ML Models/018 Perform Training and Predictions.mp4 29.2 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/013 Relational Operators & Aggregation Functions on Numpy Arrays.mp4 29.1 MB
  • 19 - Reference Getting Started with AWS/011 Creation of S3 Bucket from CLI.mp4 29.1 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/006 Array Indexing and Slicing.mp4 28.6 MB
  • 02 - Python for MLOps/009 Variables - Comments - Markdown Cells - Hands On.mp4 28.3 MB
  • 03 - Git and Github Fundamentals for MLOps/003 Local Repo vs Remote Repo.mp4 28.1 MB
  • 11 - Lnux Operating System for DevOps and Data Scientists/003 How to Launch EC2 Instances (Quick Refresh).mp4 28.0 MB
  • 19 - Reference Getting Started with AWS/010 Creation of S3 Bucket from Console.mp4 27.8 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/035 Adjusting the Plots.mp4 27.8 MB
  • 03 - Git and Github Fundamentals for MLOps/006 Concept of Working Directory - Staging Area - Commit.mp4 27.2 MB
  • 03 - Git and Github Fundamentals for MLOps/004 Git Configurations.mp4 27.2 MB
  • 02 - Python for MLOps/013 Python String - Builtin Functions - Hands On.mp4 26.2 MB
  • 05 - Packaging the ML Models/014 Fixes on Python Scripts.mp4 26.2 MB
  • 13 - Monitoring and Debugging of ML System/004 Challenge - Who Owns what.mp4 26.0 MB
  • 14 - Continuous Monitoring with Prometheus/013 Monitor the Client Application using Prometheus.mp4 25.9 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/030 Data Cleaning.mp4 25.5 MB
  • 05 - Packaging the ML Models/010 Data Preprocessing part 2.mp4 24.3 MB
  • 12 - Working with CI CD Tool Jenkins/023 Perform Test of Pipeline.mp4 24.3 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/045 Which Plot to use.mp4 23.6 MB
  • 07 - Docker for Machine Learning/007 Push the Docker Image to DockerHub.mp4 23.2 MB
  • 02 - Python for MLOps/006 Jupyter Lab Quick Tour.mp4 22.8 MB
  • 02 - Python for MLOps/015 Data Structures - Tuples.mp4 22.8 MB
  • 12 - Working with CI CD Tool Jenkins/006 Create Dockerfile.mp4 22.4 MB
  • 14 - Continuous Monitoring with Prometheus/011 Monitor the Infrastructure with Prometheus.mp4 21.3 MB
  • 02 - Python for MLOps/017 Data Structures - Sets.mp4 20.9 MB
  • 02 - Python for MLOps/021 Control Statements - Conditional Statements in Python.mp4 20.8 MB
  • 09 - Build MLApps using Streamlit/001 Introduction to Streamit.mp4 19.6 MB
  • 08 - Build MLApps using FastAPI/005 Data Validation with Pydantic.mp4 19.5 MB
  • 05 - Packaging the ML Models/017 No module named prediction_model - fix.mp4 19.5 MB
  • 07 - Docker for Machine Learning/001 Docker for Machine Learning.mp4 19.0 MB
  • 05 - Packaging the ML Models/016 Add Python Path to Windows.mp4 18.9 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/026 Accessing Google Colab.mp4 18.9 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/016 Summary of Numpy Library Journey.mp4 18.4 MB
  • 12 - Working with CI CD Tool Jenkins/014 Create your first First Jenkins Project.mp4 18.3 MB
  • 05 - Packaging the ML Models/003 Model fit and generate Predictions.mp4 17.9 MB
  • 18 - Post Productionizing ML Models/008 AB Testing.mp4 17.8 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/008 Copy Arrays.mp4 17.7 MB
  • 12 - Working with CI CD Tool Jenkins/012 Introduction to Jenkins FreeStyle Projects and Pipeline Jobs.mp4 17.2 MB
  • 02 - Python for MLOps/019 Reading the Input from Keyboard.mp4 17.1 MB
  • 19 - Reference Getting Started with AWS/006 IAM Policy.mp4 16.4 MB
  • 02 - Python for MLOps/016 Data Structures - Dictionary.mp4 15.8 MB
  • 02 - Python for MLOps/020 String Formatting.mp4 15.6 MB
  • 02 - Python for MLOps/003 Introduction to Python Programming.mp4 15.6 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/009 Mathematical Operation on Numpy Arrays.mp4 15.5 MB
  • 02 - Python for MLOps/023 List comprehension.mp4 15.2 MB
  • 05 - Packaging the ML Models/020 Testing the New Virtual Environments.mp4 15.1 MB
  • 05 - Packaging the ML Models/015 Add Python Path to MacOS.mp4 15.0 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/040 Introduction to Seaborn.mp4 14.5 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/004 Creation of Array Object - np.array().mp4 14.4 MB
  • 02 - Python for MLOps/025 Modules in Python.mp4 14.3 MB
  • 15 - Deploy Applications with Docker Compose/001 Introduction to Docker Compose.mp4 13.9 MB
  • 14 - Continuous Monitoring with Prometheus/005 Metric Types of Prometheus.mp4 13.8 MB
  • 02 - Python for MLOps/004 Install Anaconda.mp4 13.8 MB
  • 17 - Monitor the ML System with WhyLogs/005 Summary.mp4 12.9 MB
  • 02 - Python for MLOps/018 Explicit and Implicit Casting in Python Programming.mp4 12.9 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/003 Import Numpy & Access help.mp4 12.7 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/002 Basics of numpy array object.mp4 12.5 MB
  • 13 - Monitoring and Debugging of ML System/007 Operational Level Monitoring.mp4 12.3 MB
  • 17 - Monitor the ML System with WhyLogs/002 Setting Up WhyLabs.mp4 12.2 MB
  • 18 - Post Productionizing ML Models/001 Post-Productionalizing ML Models - What Next.mp4 12.0 MB
  • 03 - Git and Github Fundamentals for MLOps/016 Summary.mp4 11.8 MB
  • 14 - Continuous Monitoring with Prometheus/002 Use case on Continuous Monitoring.mp4 11.5 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/012 np.arange().mp4 11.4 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/039 Historgram Plot.mp4 11.4 MB
  • 13 - Monitoring and Debugging of ML System/002 What is Monitoring of ML models & When to Update Model in Production.mp4 11.1 MB
  • 18 - Post Productionizing ML Models/007 How to Mitigate Risk of Model Attacks.mp4 10.9 MB
  • 05 - Packaging the ML Models/024 Create Version File.mp4 10.7 MB
  • 14 - Continuous Monitoring with Prometheus/003 Introduction to Prometheus.mp4 10.7 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/005 Attributes of Numpy Array.mp4 9.5 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/025 Introduction to EDA.mp4 9.5 MB
  • 06 - Mlflow - Manage ML experiments/013 Summary.mp4 9.0 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/010 Linear Algebra Functions in Numpy.mp4 8.9 MB
  • 02 - Python for MLOps/029 Libraries in Python.mp4 8.9 MB
  • 13 - Monitoring and Debugging of ML System/008 Tools and Best Practices of Machine Learning Model Monitoring.mp4 8.7 MB
  • 12 - Working with CI CD Tool Jenkins/002 How do we Use Jenkins in MLOps.mp4 8.6 MB
  • 10 - Build MLApps using Flask/001 What is Flask.mp4 8.6 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/017 Introduction to Pandas.mp4 8.5 MB
  • 02 - Python for MLOps/028 Working with Python Scripts.mp4 7.8 MB
  • 12 - Working with CI CD Tool Jenkins/007 Exposing the Application Port as per Dockerfile.mp4 7.8 MB
  • 12 - Working with CI CD Tool Jenkins/018 Introduction to CI CT CD Pipeline.mp4 7.5 MB
  • 12 - Working with CI CD Tool Jenkins/013 Exploration of Jenkins UI.mp4 7.5 MB
  • 18 - Post Productionizing ML Models/003 Adversarial Attack.mp4 7.4 MB
  • 18 - Post Productionizing ML Models/009 Future of MLOps.mp4 7.4 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/037 Scatter Plot.mp4 7.3 MB
  • 19 - Reference Getting Started with AWS/015 Clean Up Activity.mp4 7.3 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/019 Mathematical Operation on Pandas Series.mp4 7.2 MB
  • 02 - Python for MLOps/007 Variables in Python.mp4 6.4 MB
  • 18 - Post Productionizing ML Models/002 Model Security.mp4 6.2 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/014 Boolean Masking.mp4 5.7 MB
  • 20 - Python for Data Science - Numpy - Pandas - Matplotlib - (Additional Learning)/033 Types of Plot - Line plot.mp4 5.7 MB
  • 02 - Python for MLOps/001 About the Section.mp4 5.4 MB
  • 19 - Reference Getting Started with AWS/001 What do we cover in this section.mp4 4.4 MB
  • 18 - Post Productionizing ML Models/005 Distributed Denial of Service Attack (DDOS).mp4 4.3 MB
  • 14 - Continuous Monitoring with Prometheus/007 Introduction Grafana.mp4 4.1 MB
  • 19 - Reference Getting Started with AWS/008 Delete the IAM User.mp4 4.0 MB
  • 18 - Post Productionizing ML Models/006 Data Privacy Attack.mp4 4.0 MB
  • 11 - Lnux Operating System for DevOps and Data Scientists/001 Agenda of this section.mp4 3.5 MB
  • 18 - Post Productionizing ML Models/004 Data Poisoning Attack.mp4 2.2 MB
  • 11 - Lnux Operating System for DevOps and Data Scientists/004 Basic Linux Commands of Linux.srt 142.3 kB
  • 21 - Additional Learning on Topic of MLOps/004 Generative AI and Prompt Engineering Introduction.srt 100.4 kB
  • 21 - Additional Learning on Topic of MLOps/005 Bonus Understanding Transformer Architecture.srt 72.7 kB
  • 21 - Additional Learning on Topic of MLOps/001 MLOps with MLFlow in 1 Hour.srt 71.1 kB
  • 17 - Monitor the ML System with WhyLogs/003 Whylogs - Drift Detection, Input, Output, Bias Monitoring.srt 66.3 kB
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