How https-deeplearning-ai/machine-learning-engineering-for-production-public works
This repository is a collection of public learning resources for deeplearning.ai’s Machine Learning Engineering for Production specialization, not a single executable product. Learners explore model development and analysis, then production topics such as serving, orchestration, and delivery. The graph groups representative labs by topic; notebook contents and most inter-lab wiring were not inspected, so the edges show learner access rather than an implied technical pipeline.
Main entry points: C1W2_Ungraded_Lab_Birds_Cats_Dogs.ipynb Image classification · C2_W4_Lab_1_WeatherData.ipynb Time series · C2_W4_Lab_2_Signals.ipynb Signal processing · C3_W1_Lab_1_Keras_Tuner.ipynb Hyperparameter tuning
Components 20
Model development
- Image classification
course1/week2-ungraded-lab/C1W2_Ungraded_Lab_Birds_Cats_Dogs.ipynb - Time series
course2/week4-ungraded-lab/C2_W4_Lab_1_WeatherData.ipynb - Signal processing
course2/week4-ungraded-lab/C2_W4_Lab_2_Signals.ipynb - Hyperparameter tuning
course3/week1-ungraded-lab/C3_W1_Lab_1_Keras_Tuner.ipynb - Dimensionality reduction
course3/week2-ungraded-lab - Compression and pruning
course3/week2-ungraded-lab/C3_W2_Lab_3_Quantization_and_Pruning.ipynb - Distributed training
course3/week3-ungraded-lab/C3_W3_Lab_1_Distributed_Training.ipynb - Knowledge distillation
course3/week3-ungraded-lab/C3_W3_Lab_2_Knowledge_Distillation.ipynb
Evaluation and analysis
- TFX evaluation
course3/week4-ungraded-lab - Fairness indicators
course3/week4-ungraded-lab/C3_W4_Lab_3_Fairness_Indicators.ipynb - Model explainability
course3/week5-ungraded-lab
Serving and data
- Wine prediction API
course4/week2-ungraded-labs/C4_W2_Lab_1_FastAPI_Docker/with-batch/app/main.py - Kubernetes serving
course4/week2-ungraded-labs/C4_W2_Lab_2_Intro_to_Kubernetes - Beam ETL
course4/week2-ungraded-labs/C4_W2_Lab_4_ETL_Beam/C4_W2_Lab_4_Apache_Beam_and_Tensorflow.ipynb
Pipelines and operations
- Kubeflow Pipelines
course4/week3-ungraded-labs/C4_W3_Lab_1_Intro_to_KFP/C4_W3_Lab_1_Kubeflow_Pipelines.ipynb - Custom TFX components
course4/week3-ungraded-labs/C4_W3_Lab_2_TFX_Custom_Components.ipynb - Model versioning
course4/week3-ungraded-labs/C4_W3_Lab_3_TFS_Model_Versioning - GitHub Actions
course4/week3-ungraded-labs/C4_W3_Lab_4_Github_Actions/app/main.py - Latency testing
course4/week2-ungraded-labs/C4_W2_Lab_3_Latency_Test_Compose/locustfile.py
Other components
- Learner
Connections 19
- Learner → Image classification: studies
- Learner → Time series: studies
- Learner → Signal processing: studies
- Learner → Hyperparameter tuning: studies
- Learner → Dimensionality reduction: studies
- Learner → Compression and pruning: studies
- Learner → Distributed training: studies
- Learner → Knowledge distillation: studies
- Learner → TFX evaluation: studies
- Learner → Fairness indicators: studies
- Learner → Model explainability: studies
- Learner → Wine prediction API: studies
- Learner → Kubernetes serving: studies
- Learner → Beam ETL: studies
- Learner → Kubeflow Pipelines: studies
- Learner → Custom TFX components: studies
- Learner → Model versioning: studies
- Learner → GitHub Actions: studies
- Learner → Latency testing: studies