Posts

Showing posts from April, 2023

SQL Joins

-
Image
Joins are used to combine rows from two or more tables based on related columns between them. Joins allow you to retrieve data from multiple tables simultaneously, enabling you to create complex queries that fetch data from different sources. There are different types of joins in SQL, including: INNER JOIN Returns only the rows that have matching values in both tables based on the specified join condition. It discards non-matching rows from both tables. Example:           create table t1(x int); insert into t1 values(1); insert into t1 values(1); insert into t1 values(0); create table t2(y int); insert into t2 values(0); insert into t2 values(1); insert into t2 values(1);           select * from t1 inner join t2 on t1.x = t2.y Output: 2. LEFT JOIN (or) LEFT OUTER JOIN Returns all the rows from the left (or first) table and the matching rows from the right (or second) table. If there is no match, NULL values are
Post a Comment
Read more

MLFlow Serving Custom Models in production environment

-
Image
  Serve Word2vec pretrained model using pyfunc flavor through docker. After completing development, if you want to serve your trained model, then it has to be either logged or saved via log_model()/save_model() function using one of the built-in flavors. MLflow does support multiple built-in flavors such as sklearn, keras etc and the flavor type is saved in the MLmodel file. Below is the example to save the model using sklearn flavor. mlflow . sklearn . log_model(sk_model, "sk_models") Flavors are the key concepts which makes MLflow more powerful. Flavors are a convention that deployment tools can use to understand the model, which makes it possible to write tools that work with models from any ML library without having to integrate each tool with each library. And the below command helps to expose the logged model as a service mlflow models serve -m ‘runs:/616e1e58d5814be58f613f13dfd8e9de/’ -h 0.0.0.0 -p 8000 And you can access the exposed model in the postman like this. htt
Post a Comment
Read more