Categories
2022
Apache Kafka 101
Chapter 9. Continual Learning and Test in Production
Chapter 8. Data Distribution Shifts and Monitoring
Chapter 7. Model Deployment and Prediction Service
Chapter 3. Data Engineer Fundamentals
[ Chapter 4. Model API ] 4) Docker without model
[ Chapter 4. Model API ] 3) Docker with model
[ Chapter 4. Model API ] 2) Write Data to DB
[ Chapter 4. Model API ] 1) API with Model
[ Chapter 3. API ] 5) Build FastAPI Docker
[ Chapter 3. API ] 4) FastAPI with Postgresql
[ Chapter 3. API ] 3) FastAPI CRUD with Pydantic
[ Chapter 3. API ] 2) FastAPI CRUD
![[ Chapter 3. API ] 2) FastAPI CRUD](/blog/p/chapter-3.-api-2-fastapi-crud/swagger_hu1247325439913060603.png)
[ Chapter 2. Model Registry ] 4) Download Model from MLFlow
[ Chapter 2. Model Registry ] 3) Train Model and Save to MLFlow
![[ Chapter 2. Model Registry ] 3) Train Model and Save to MLFlow](/blog/p/chapter-2.-model-registry-3-train-model-and-save-to-mlflow/run_hu13074674388358592129.png)
[ Chapter 2. Model Registry ] 2) Get Data from DB
[ Chapter 2. Model Registry ] 1) Run Mlflow Server
![[ Chapter 2. Model Registry ] 1) Run Mlflow Server](/blog/p/chapter-2.-model-registry-1-run-mlflow-server/mlflow-ui_hu11472424883553230026.png)