Snowflake SnowPro Core
Snowflake SnowPro Core is one of the certification exams offered by Snowflake as part of the SnowPro certification program. It is designed for individuals who have experience working with Snowflake and focuses on core concepts and functionality of the Snowflake platform. The exam covers topics such as data loading, querying, data modeling, security, performance, and resource management. To earn the Snowflake SnowPro Core certification, individuals must pass the SnowPro Core exam.
AI Context for the day – 8th December 2021
ML context for the day – 18th August 2021
Simple linear regression
y = mx + c
y – Dependent variable(DV)
x – Independent variable(IV)
c – constant
AI Context for the day – 6th August 2021
Training set and Test set
Filling missing data using scikit
from sklearn.impute import SimpleImputer
We are importing the simple imputer from scikit library.
imputer = SimpleImputer(missing_values=np.nan, strategy=’mean’)
The strategy used is mean, where the missing data is replaced by average of the values.
imputer.fit(X[:, 1:3])
The number of columns on which the above function is used is 2 i.e between 1 and 3.
X[:, 1:3] = imputer.transform(X[:, 1:3])
The new column is again assigned to the 2 columns.
Importing dataset in Python
dataset = [library alias name].read_csv(‘file.csv’)
x = dataset.iloc[:,:-1].values
y = dataset.iloc[:, -1].values
In the above lines, read_csv and iloc are functions.
[:,:-1] is slicing range of the values.
Importing libraries in Python
Syntax
import [library] as []