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Learn to Build Machine Learning Systems That Don t Suck

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Files:

Get Bonus Downloads Here.url 183 bytes
001 - Lesson 1 - Getting Started.mp4 122.6 MB
002 - Lesson 2 - Preparing Your Local Environment.mp4 128.3 MB
003 - Lesson 3 - Introduction to Metaflow.mp4 132.3 MB
004 - Lesson 4 - Training the Model.mp4 161.9 MB
005 - Lesson 5 - The Training Pipeline.mp4 303.3 MB
006 - Lesson 6 - Building a Custom Inference Process.mp4 187.6 MB
007 - Lesson 7 - Deploying The Model.mp4 118.2 MB
008 - Lesson 8 - The Endpoint Pipeline.mp4 170.3 MB
009 - Lesson 9 - Monitoring The Model.mp4 85.2 MB
010 - Lesson 10 - The Monitoring Pipeline.mp4 122.6 MB
011 - Lesson 11 - Production Pipelines in Amazon Web Services.mp4 180.8 MB
012 - Lesson 12 - Deploying the Model to SageMaker.mp4 107.6 MB
013 - Lesson 13 - The Deployment Pipeline.mp4 116.8 MB
014 - Lesson 14 - Monitoring the SageMaker Endpoint.mp4 46.2 MB
015 - Lesson 15 - Running Pipelines Remotely.mp4 152.6 MB
016 - Session 1 - Introduction and Initial Setup.mp4 322.9 MB
017 - Session 2 - Exploratory Data Analysis.mp4 145.5 MB
018 - Session 3 - Splitting and Transforming the Data.mp4 403.5 MB
019 - Session 4 - Training the Model.mp4 281.5 MB
020 - Session 5 - Custom Training Container.mp4 168.0 MB
021 - Session 6 - Tuning the Model.mp4 121.5 MB
022 - Session 7 - Evaluating the Model.mp4 156.1 MB
023 - Session 8 - Registering the Model.mp4 77.4 MB
024 - Session 9 - Conditional Registration.mp4 64.3 MB
025 - Session 10 - Serving the Model.mp4 88.7 MB
026 - Session 11 - Deploying the Model.mp4 86.8 MB
027 - Session 12 - Deploying From the Pipeline.mp4 230.2 MB
028 - Session 13 - Deploying From an Event.mp4 75.6 MB
029 - Session 14 - Building an Inference Pipeline.mp4 159.4 MB
030 - Session 15 - Custom Inference Script.mp4 114.3 MB
031 - Session 16 - Data Quality Baseline.mp4 102.2 MB
032 - Session 17 - Model Quality Baseline.mp4 102.8 MB
033 - Session 18 - Data Monitoring.mp4 130.0 MB
034 - Session 19 - Model Monitoring.mp4 73.2 MB
035 - Session 20 - Shadow Deployments.mp4 65.7 MB
Bonus Resources.txt 70 bytes
Building Machine Learning Systems That Don't Suck (1).html 480.4 KB
Building Machine Learning Systems That Don't Suck (10).html 470.9 KB
Building Machine Learning Systems That Don't Suck (11).html 471.5 KB
Building Machine Learning Systems That Don't Suck (12).html 472.0 KB
Building Machine Learning Systems That Don't Suck (13).html 466.8 KB
Building Machine Learning Systems That Don't Suck (14).html 472.8 KB
Building Machine Learning Systems That Don't Suck (15).html 470.5 KB
Building Machine Learning Systems That Don't Suck (16).html 519.7 KB
Building Machine Learning Systems That Don't Suck (17).html 512.6 KB
Building Machine Learning Systems That Don't Suck (18).html 512.9 KB
Building Machine Learning Systems That Don't Suck (19).html 515.6 KB
Building Machine Learning Systems That Don't Suck (2).html 478.1 KB
Building Machine Learning Systems That Don't Suck (20).html 518.2 KB
Building Machine Learning Systems That Don't Suck (21).html 512.9 KB
Building Machine Learning Systems That Don't Suck (22).html 511.1 KB
Building Machine Learning Systems That Don't Suck (23).html 521.2 KB
Building Machine Learning Systems That Don't Suck (24).html 521.9 KB
Building Machine Learning Systems That Don't Suck (25).html 520.5 KB
Building Machine Learning Systems That Don't Suck (26).html 509.0 KB
Building Machine Learning Systems That Don't Suck (27).html 517.5 KB
Building Machine Learning Systems That Don't Suck (28).html 520.8 KB
Building Machine Learning Systems That Don't Suck (29).html 513.7 KB
Building Machine Learning Systems That Don't Suck (3).html 444.5 KB
Building Machine Learning Systems That Don't Suck (30).html 502.9 KB
Building Machine Learning Systems That Don't Suck (31).html 512.1 KB
Building Machine Learning Systems That Don't Suck (32).html 513.4 KB
Building Machine Learning Systems That Don't Suck (33).html 514.2 KB
Building Machine Learning Systems That Don't Suck (34).html 504.2 KB
Building Machine Learning Systems That Don't Suck (35).html 504.5 KB
Building Machine Learning Systems That Don't Suck (4).html 477.4 KB
Building Machine Learning Systems That Don't Suck (5).html 442.7 KB
Building Machine Learning Systems That Don't Suck (6).html 474.6 KB
Building Machine Learning Systems That Don't Suck (7).html 474.0 KB
Building Machine Learning Systems That Don't Suck (8).html 470.5 KB
Building Machine Learning Systems That Don't Suck (9).html 472.7 KB
Building Machine Learning Systems That Don't Suck.html 975.8 KB
github.txt 89 bytes
LICENSE 11.1 KB
README.md 39.2 KB
cohort.ipynb 463.3 KB
Dockerfile 495 bytes
ml-dependencies.yml 154 bytes
basic-model.png?43858?v=1.05 165.3 KB
condition-step.png?43858?v=1.05 222.9 KB
culmen.jpeg 268.8 KB
data-quality-baseline.png?43858?v=1.05 92.7 KB
deploy-step.png?43858?v=1.05 225.0 KB
deploying-flask.png?43858?v=1.05 219.2 KB
deploying-from-event.png?43858?v=1.05 171.4 KB
deploying-model.png?43858?v=1.05 184.3 KB
diagram.png?43858?v=1.05 488.6 KB
endpoint.png?43858?v=1.05 156.9 KB
evaluation-step.png?43858?v=1.05 167.1 KB
inference-pipeline.png?43858?v=1.05 243.6 KB
model-quality-baseline.png?43858?v=1.05 231.6 KB
penguins.png?43858?v=1.05 2.8 MB
processing-job.png?43858?v=1.05 294.7 KB
processing-step.png?43858?v=1.05 185.9 KB
registration-step.png?43858?v=1.05 186.4 KB
shadow-deployment.png?43858?v=1.05 245.2 KB
training-job.png?43858?v=1.05 297.0 KB
training-step.png?43858?v=1.05 162.7 KB
tuning-job.png?43858?v=1.05 211.0 KB
tuning-step.png?43858?v=1.05 166.9 KB
penguins.flow 24.4 KB
mlflow-cfn.yaml 2.5 KB
mlschool-cfn.yaml 6.9 KB
penguins.csv 13.2 KB
example.env 769 bytes
gitignore 207 bytes
idx-template.js?v=1.05on 689 bytes
idx-template.nix 870 bytes
dev.nix 2.4 KB
icon.png?43858?v=1.05 8.1 KB
architecture.png?43858?v=1.05 655.5 KB
monitoring.png?43858?v=1.05 377.1 KB
penguins.png?43858?v=1.05 2.8 MB
training.png?43858?v=1.05 411.6 KB
justfile 1.9 KB
logging.conf 566 bytes
markdownlint.js?v=1.05on 98 bytes
mlschool-toc.js?v=1.05on 432 bytes
__init__.py 0 bytes
common.py 5.8 KB
deployment.py 20.8 KB
endpoint.py 10.8 KB
inference.py 9.9 KB
monitoring.py 12.3 KB
sagemaker.py 5.6 KB
training.py 18.6 KB
tuning.py 3.6 KB
pyproject.toml 532 bytes
requirements.txt 214 bytes
__init__.py 0 bytes
test_inference.py 6.5 KB
settings.js?v=1.05on 283 bytes
cohort.ipynb 463.3 KB
Dockerfile 495 bytes
ml-dependencies.yml 154 bytes
basic-model.png?43858?v=1.05 165.3 KB
condition-step.png?43858?v=1.05 222.9 KB
culmen.jpeg 268.8 KB
data-quality-baseline.png?43858?v=1.05 92.7 KB
deploy-step.png?43858?v=1.05 225.0 KB
deploying-flask.png?43858?v=1.05 219.2 KB
deploying-from-event.png?43858?v=1.05 171.4 KB
deploying-model.png?43858?v=1.05 184.3 KB
diagram.png?43858?v=1.05 488.6 KB
endpoint.png?43858?v=1.05 156.9 KB
evaluation-step.png?43858?v=1.05 167.1 KB
inference-pipeline.png?43858?v=1.05 243.6 KB
model-quality-baseline.png?43858?v=1.05 231.6 KB
penguins.png?43858?v=1.05 2.8 MB
processing-job.png?43858?v=1.05 294.7 KB
processing-step.png?43858?v=1.05 185.9 KB
registration-step.png?43858?v=1.05 186.4 KB
shadow-deployment.png?43858?v=1.05 245.2 KB
training-job.png?43858?v=1.05 297.0 KB
training-step.png?43858?v=1.05 162.7 KB
tuning-job.png?43858?v=1.05 211.0 KB
tuning-step.png?43858?v=1.05 166.9 KB
penguins.flow 24.4 KB

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