Machine Learning Ops on Google CloudReal World Data Science

Files Included :

1 Hello & Introduction.mp4 (26.79 MB)
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2 Discord Server for this Course.mp4 (2.98 MB)
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3 Lab-Create GCP Trial Account for the course.mp4 (8.23 MB)
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4 Lab-Download gcloud-cli & project configuration.mp4 (14.04 MB)
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5 Course prerequisites and installations.mp4 (8.54 MB)
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6 Course Overview & section walkthrough.mp4 (10.8 MB)
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7 GCP Services used in the course.mp4 (4.81 MB)
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1 Introduction To ML-Ops.mp4 (15.06 MB)
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2 Key Components Principles in ML-Ops.mp4 (10.12 MB)
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1 Introduction to CICD on GCP.mp4 (16.39 MB)
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10 Lab Setup Cloudbuild Triggers from GitHub Repo.mp4 (31.15 MB)
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11 XGBoost Model Overview for Coupon Recommendations Model.mp4 (38.92 MB)
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12 Lab Deploy and implement Model Serving Flask Application and Pytest Locally.mp4 (52.41 MB)
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13 Lab Deploy ML Model to CloudRun using CloudBuild.mp4 (31.3 MB)
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14 Overview of AB Testing for ML Models using CloudRun.mp4 (11.85 MB)
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15 Lab Deploy New Version of ML Model & Update version traffic.mp4 (37.5 MB)
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16 Assignment - Deploy Bike Rentals Regression Model & perform CICD.mp4 (14.53 MB)
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2 Introduction to GCP Container Registry and Artifact Registry.mp4 (10.53 MB)
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3 Lab Enable necessary APIs and install modules.mp4 (17.88 MB)
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4 Introduction To GCP CloudRun for ML Models.mp4 (12.73 MB)
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5 Overview of Steps for Flask Application - Local development.mp4 (5.37 MB)
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6 Lab Deploy Flask application using ContainerArtifact Registry and CloudRun.mp4 (80.05 MB)
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7 Lab Execute PyTest locally using ChatGPT.mp4 (26.79 MB)
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8 Introduction to GCP CloudBuild Service.mp4 (8.72 MB)
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9 Lab Deploy Flask application using GCP CloudBuild.mp4 (29.1 MB)
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1 Overview of Data science model for Bank Marketing Campaign.mp4 (27.62 MB)
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10 Overview of CICD for Model Training.mp4 (5.53 MB)
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11 Lab CICD of Model Training Code using Cloud-Build,PyTest and Github.mp4 (65.34 MB)
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12 Lab Setup CloudBuild triggers.mp4 (23.99 MB)
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13 Assignment Part-1 Setup Continuous Training for a Marketing ROI Model.mp4 (13.88 MB)
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14 Assignment Part-2 Perform CICD of the Data Science ROI Model.mp4 (6.66 MB)
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15 Assignment Part-3 Deploy Model Serving Application to GCP CloudRun.mp4 (15.02 MB)
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2 Introduction to Continuous Training.mp4 (12.71 MB)
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3 Introduction to Airflow For Continuous Training.mp4 (8.97 MB)
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4 Lab Create Setup Airflow composer Env and Vertex AI Workbench.mp4 (26.6 MB)
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5 Lab Execute Model Training using Jupyter-Nbk on GCP.mp4 (44.76 MB)
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6 Lab Execute Airflow Dag for Machine Learning Workflow.mp4 (69.45 MB)
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7 Lab Continuous Training Pipeline in Action.mp4 (12.39 MB)
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8 Implications of Failure scenarios in Continuous Training.mp4 (10.38 MB)
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9 Lab Trigger Continuous Training to capture model logs and setup alerting.mp4 (53.24 MB)
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1 Section Overview.mp4 (3.6 MB)
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10 Lab Overview of CICD using Vertex AI.mp4 (7.28 MB)
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11 Lab Vertex AI CICD of Data science model using CloudBuild.mp4 (59.14 MB)
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12 Assignment Deploy XGBoost Model to Vertex AI.mp4 (13.75 MB)
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2 Introduction to Vertex AI Model Training Service.mp4 (12.18 MB)
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3 Overview of Bike Share Rentals Regression Model.mp4 (11.8 MB)
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4 Lab Vertex AI Model Training using Web Console and Gcloud CLI.mp4 (74.49 MB)
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5 Introduction to Vertex AI Model Registry.mp4 (10.28 MB)
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6 Lab Python SDK-Vertex AI Model Training,Model Registry and Model Deployment.mp4 (80.91 MB)
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7 Lab Execute Online & Batch prediction Service using Python SDK and jupter nbks.mp4 (27.07 MB)
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8 Lab-Walkthrough Batch Prediction Output & Online Prediction jobs using Cloud Run.mp4 (64.39 MB)
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9 Lab-Deploy and implement Batch Prediction Job using GCP Cloud Functions.mp4 (50.22 MB)
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1 Introduction to Kubeflow for ML Orchestration.mp4 (10.01 MB)
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10 Assignment Perform Experiments for Bike share Regression Model.mp4 (4.27 MB)
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2 Different Components in Kubeflow Pipelines.mp4 (18.04 MB)
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3 Lab Deploy a simple pipeline for XgBoost Model.mp4 (92.16 MB)
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4 Lab Trigger Xgboost Model using compiled json for continuous training.mp4 (31.81 MB)
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5 Lab Execute end-to-end kubeflow pipeline with model evaluation.mp4 (29.36 MB)
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6 Lab Assignment Deploy a Scikit-Learn Credit Scoring Model to Vertex Pipelines.mp4 (13.92 MB)
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7 Introduction to Vertex AI Experiments.mp4 (9.67 MB)
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8 Lab Use different model hyperparameters for Xgboost with Vertex AI Experiments.mp4 (51.67 MB)
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9 LabTrain Different Data science Classification models using Experiments.mp4 (39.46 MB)
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1 Introduction to Hyperparameter Tuning on Vertex AI.mp4 (11.36 MB)
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10 Lab Deploy different versions of XgBoost Model to Model Registry.mp4 (76.44 MB)
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11 Introduction to Vertex AI FeatureStore.mp4 (15.6 MB)
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12 Lab Create Feature store objects.mp4 (29.06 MB)
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13 Lab Ingest Data from Pandas DF into Feature Store.mp4 (43.3 MB)
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14 Lab Read Data From Vertex AI Feature Store into Pandas Df.mp4 (57.98 MB)
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15 Introduction to AutoML.mp4 (6.6 MB)
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16 Lab-Train and Deploy Classification Model using AutoML.mp4 (38.84 MB)
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17 Lab - Train and Deploy Regression Model using AutoML.mp4 (34.55 MB)
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2 Lab Implement Hyperparameter Tuning for BikeShare Regression Model.mp4 (67.82 MB)
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3 Lab Result Walkthrough & Assignment Overview.mp4 (10.03 MB)
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4 Lab Result Walkthrough & Assignment Overview.mp4 (17.32 MB)
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5 Lab Deploy Model Endpoint With Explainability Parameters.mp4 (37.87 MB)
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6 Lab Execute explainability for online predictions and Interpret results.mp4 (40.07 MB)
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7 Lab Execute explainability for online predictions and Interpret results.mp4 (17.89 MB)
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8 Assignment Perform Explainability for XgBoost Models.mp4 (6.69 MB)
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9 Introduction to Model Versioning using Vertex AI Model Registry.mp4 (6.66 MB)
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1 Introduction to Generative AI.mp4 (28.94 MB)
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2 Introduction to Large language models - PaLM 2.mp4 (7.35 MB)
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3 Important keywords and concepts in LLM.mp4 (16.12 MB)
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4 Lab-Generative AI Studio.mp4 (39.62 MB)
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5 Lab - Execute LLM using Python & Jupyter Nbk.mp4 (34.11 MB)
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6 Lab - Deploy text classification LLM Model using Python & Cloud Run.mp4 (38.7 MB)
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7 Lab-Deploy Document Summarization Application using Python & Cloud Run.mp4 (33.02 MB)
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8 Lab- Generate Fashion Image Descriptions using Python.mp4 (41.85 MB)
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