Podcast
Questions and Answers
What does a descriptive model in data modeling examine?
What does a descriptive model in data modeling examine?
- The preferences based on past actions (correct)
- The probability of yes/no outcomes
- The correlation between unrelated variables
- The likelihood of future events
What is the purpose of a training set in predictive modeling?
What is the purpose of a training set in predictive modeling?
- To act as a gauge for model calibration (correct)
- To determine the final outcome of the model
- To provide a set of unknown outcomes
- To replace the need for algorithms
What does a predictive model in data modeling try to yield?
What does a predictive model in data modeling try to yield?
- Yes/no or stop/go outcomes (correct)
- Statistical analysis
- Descriptive outcomes
- Machine learning algorithms
What is the role of a data scientist in the modeling stage?
What is the role of a data scientist in the modeling stage?
What is crucial for the success of data compilation, preparation and modeling?
What is crucial for the success of data compilation, preparation and modeling?
The train-test split is a technique for evaluating the performance of a machine learning algorithm. It can be used for ______ or regression problems and can be used for any supervised learning algorithm.
The train-test split is a technique for evaluating the performance of a machine learning algorithm. It can be used for ______ or regression problems and can be used for any supervised learning algorithm.
The procedure involves taking a dataset and dividing it into two ______. The first subset is used to fit the model and is referred to as the training dataset.
The procedure involves taking a dataset and dividing it into two ______. The first subset is used to fit the model and is referred to as the training dataset.
The second subset is not used to train the model; instead, the input element of the dataset is provided to the model, then predictions are made and compared to the expected values. This second dataset is referred to as the ______ dataset.
The second subset is not used to train the model; instead, the input element of the dataset is provided to the model, then predictions are made and compared to the expected values. This second dataset is referred to as the ______ dataset.
Train Dataset: Used to fit the machine learning ______.
Train Dataset: Used to fit the machine learning ______.
Test Dataset: Used to evaluate the fit machine learning ______.
Test Dataset: Used to evaluate the fit machine learning ______.
Train-test split is a technique for evaluating the performance of a machine learning algorithm. It can be used for ______ or regression problems and can be used for any supervised learning algorithm.
Train-test split is a technique for evaluating the performance of a machine learning algorithm. It can be used for ______ or regression problems and can be used for any supervised learning algorithm.
The objective is to estimate the performance of the machine learning model on new data: data not used to train the model.
The objective is to estimate the performance of the machine learning model on new data: data not used to train the model.
The first subset is used to fit the model and is referred to as the ______ dataset.
The first subset is used to fit the model and is referred to as the ______ dataset.
Train Dataset: Used to fit the machine learning ______.
Train Dataset: Used to fit the machine learning ______.
Test Dataset: Used to evaluate the fit machine learning ______.
Test Dataset: Used to evaluate the fit machine learning ______.
Study Notes
Data Modeling
- A descriptive model in data modeling examines a snapshot of the current situation, providing a detailed description of the data and its relationships.
Predictive Modeling
- A predictive model in data modeling tries to yield a forecast of the future situation, providing predictions or probabilities of future outcomes.
Role of a Data Scientist
- The role of a data scientist in the modeling stage is crucial for the success of data compilation, preparation, and modeling.
Train-Test Split
- The train-test split is a technique for evaluating the performance of a machine learning algorithm, which can be used for classification or regression problems and any supervised learning algorithm.
- The procedure involves taking a dataset and dividing it into two subsets: a training dataset and a testing dataset.
- The training dataset is used to fit the model, while the testing dataset is used to evaluate the fit machine learning model.
- The objective of the train-test split is to estimate the performance of the machine learning model on new data, which is not used to train the model.
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Description
Test your knowledge of Data Modeling and learn about descriptive and predictive models. Explore how descriptive models analyze preferences and predictive models yield outcomes. Discover the different analytic approaches used, such as statistical and machine learning driven methods.
