Alteryx Machine Learning case studies
Alteryx Machine Learning · Put your knowledge to work in context.
The Alteryx Machine Learning certification validates that a practitioner can take a business question through the full Alteryx Machine Learning workflow: framing the problem, preparing and engineering features, training and tuning models, evaluating and interpreting results, deploying predictions back into Alteryx workflows, and applying responsible-AI practices. It suits analysts and citizen data scientists who already build data pipelines in Alteryx Designer and want to add automated machine learning without writing code, as well as modellers who need to explain and govern their results. The Alteryx Machine Learning case studies are 5 cases and about 2,039 words.
1Predicting Loan Default with Imbalanced Data
A financial institution wants to predict loan default using historical data of 50,000 loans, of which only 2% defaulted. They plan to use Alteryx Machine Learning to build a classification model.
418 words, about 2 min2Feature Engineering for Customer Churn Prediction
A telecom company wants to predict customer churn using a dataset with 10,000 customers and 50 features, including demographics, usage metrics, and service calls. The dataset has missing values in several columns (up to 20% missing in 'average monthly data usage'), and some categorical variables with high cardinality (e.g., 'zip code' with 1,000 unique values).
437 words, about 2 min3Model Selection and Hyperparameter Tuning for Sales Forecasting
A retail company wants to forecast weekly sales for 100 stores using historical data of 3 years. They have features like promotions, holidays, and store attributes.
405 words, about 2 min4Model Evaluation and Interpretation for Medical Diagnosis
A hospital uses Alteryx Machine Learning to build a model that predicts the likelihood of a patient having a disease based on lab results and demographics. The model will be used as a screening tool to prioritize patients for further testing.
388 words, about 2 min5Deploying a Model to Production and Monitoring
A marketing team has built a propensity model in Alteryx Machine Learning to predict which customers are likely to respond to a campaign. The model will be used to score a daily list of 10,000 customers.
391 words, about 2 min