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Explore the Data Science use cases that demonstrate how the SnapLogic machine learning Snap Packs can help solve complex data problems.

• 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.