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Databricks Certified Professional Data Scientist Exam
- Topic 1: A intermediate understanding of the steps in the machine learning lifecycle/ Model training, selection, and production A complete understanding of the basics of machine learning/ in-sample vs. out-of sample data
- Topic 2: Applied statistics concepts/ bias-variance tradeoff
- Topic 3: A complete understanding of basic machine learning algorithms and techniques/ Unsupervised techniniques like K-means and PCA
- Topic 4: A complete understanding of the basics of machine learning model management/ Linear, logistic, and regularized regression
- Topic 5: Tree-based models like decision trees, random forest and gradient boosted trees/ Categories of machine learning
- Topic 6: Specific algorithms like ALS for recommendation and isolation forests for outlier detection/ Logging and model organization with MLflow
Free Databricks Databricks Certified Professional Data Scientist Exam Exam Actual Questions
The questions for Databricks Certified Professional Data Scientist Exam were last updated On Apr. 07, 2024
Suppose there are three events then which formula must always be equal to P(E1|E2,E3)?
In which phase of the data analytics lifecycle do Data Scientists spend the most time in a project?
You are working in a data analytics company as a data scientist, you have been given a set of various types of Pizzas available across various premium food centers in a country. This data is given as numeric values like Calorie. Size, and Sale per day etc. You need to group all the pizzas with the similar properties, which of the following technique you would be using for that?
Under which circumstance do you need to implement N-fold cross-validation after creating a regression model?
Refer to the exhibit.
You are building a decision tree. In this exhibit, four variables are listed with their respective values of info-gain.
Based on this information, on which attribute would you expect the next split to be in the decision tree?
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