Systems | Development | Analytics | API | Testing

Python is insanely popular among machine learning enthusiasts these days. Hence, anyone developing a machine learning model normally turns to Python. The real challenge arises at the deployment stage because you can use many frameworks. Figuring out which Python framework to use may add to the confusion. This post discusses two popular machine learning frameworks, Flask and Django. We’ll also compare them side by side, so that you can make the right choice.

Sometimes you may want to limit the amount of analytics data coming into Moesif. This could be because you want to exclude specific traffic, such as internal or health check traffic, or you may want to reduce unnecessary data to control cost. Dynamic Sampling, available to customers on our Enterprise plan, was built to do just this. Dynamic Sampling lets you control which API calls are logged to Moesif based on customer or API behavior.

Machine learning is used across industries and user communities for a wide variety of predictive analytics needs – use cases ranging from sales forecasting to churn reduction, customer lifetime value, inventory optimization, capital allocation and more.