Pickl AI
JANUARY 3, 2024
EDA, imputation, encoding, scaling, extraction, outlier handling, and cross-validation ensure robust models. Feature importance from trees Objective: Leveraging decision tree-based models to assess feature importance. Steps of Feature Engineering 1.
Pickl AI
FEBRUARY 12, 2024
Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. What is cross-validation, and why is it used in Machine Learning?
Heartbeat
MAY 29, 2023
It is also essential to evaluate the quality of the dataset by conducting exploratory data analysis (EDA), which involves analyzing the dataset’s distribution, frequency, and diversity of text. Use a representative and diverse validation dataset to ensure that the model is not overfitting to the training data.
Expert insights. Personalized for you.
52 
Let's personalize your content