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.
| Title | Description |
|---|---|
| Iris Flower Classification | 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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