Explore the Data Science use cases that demonstrate how the SnapLogic machine learning Snap Packs can help solve complex data problems.
The table below list the use cases.
Build
- : Build a model to classify a flower based on the size of its sepal and petal.
- Iris Flower Classification using Neural Networks
- : Build a model to classify a flower based on the size of its sepal and petal.
- Diabetes Progression Prediction
- : Build a model to predict diabetes progression based on the patient's demographic and serum measurements.
- Telco Customer Churn Prediction
- : Build a model to predict the churn rate of customers based on demographic and subscription history.
- Sentiment Analysis Using SnapLogic Data Science
- : Build a sentiment analysis model using review data from Yelp.
- Lending Club Loan Approval
- : Build a model to predict the rate at which a loan will be charged-off.
- Kickstarter Project Success Prediction
- : Build a model to predict the success rate of a Kickstarter project based on the project information.
- Handwritten Digit Recognition
- : Build a convolutional neural networks model to classify handwritten digit.
- Image Recognition (Inception-v3)
- : Use Inception-v3 model to identify objects in images.
- Natural Language Processing
- : Use TextBlob library to perform simple NLP operations.
- Speech Recognition
- : Use the DeepSpeech library to transcribe audio.
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In this Section
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