Remove De-duplication Remove Frequency Remove Review Remove Validation

Machine Learning Problems: The Easy Parts

Contify

As a programmer with data science background, my attention is invariably caught by the real-world situations where machine learning algorithms have made a difference, for example: email spam filtering, news categorization, review based recommendations, social media sentiments etc. So, we implemented de-duplication algorithms to significantly reduce the resources required to process the information in these documents. Inverse document frequency.

Machine Learning Problems: The Easy Parts

Contify

As a programmer with data science background, my attention is invariably caught by the real-world situations where machine learning algorithms have made a difference, for example: email spam filtering, news categorization, review based recommendations, social media sentiments etc. So, we implemented de-duplication algorithms to significantly reduce the resources required to process the information in these documents. Inverse document frequency.

14 Quick Tips for Kick-Ass Lead Management

Hubspot

Determine the validity of a lead. We definitely recommend de-duplicating leads based on email address at the very least, but you should also verify information such as zip code, phone number, and email address when possible to keep lead records up to date, and thus, functional. Watch how leads respond to the type of content you deliver, the method of communication, and the frequency and timing of the communication to improve your lead nurturing and shorten the sales cycle.