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Why do creators need new ways to monetize?

Today, creator’s platform like YouTube enable makers to win money through
advertisement, yet there are a few prerequisites and brand well-being strategies that should be followed keeping in mind the end goal to qualify.
A content maker would need a considerable number of perspectives with a specific goal to profit by any means.
Corporate sponsorship is another valid alternative for content monetization on social media platforms.

Why are geospatial companies focusing on delivering great content?

The diverse range of potential customers today is a big challenge for geo-spatial
Only providing technical information will not have a big effect with the majority of potential customers who do not have a strong technical background.

Therefore, many geo-spatial companies now are focused on write blogs, share articles and produce detailed case studies about projects to inform potential customers about how their solutions can be used, in an easy way in order to let them understand better the technology offers. analytics-960x960_c.jpg

Where can I start with industrial analytics?

The value of industrial analytics is in the results of what they are able to deliver.
Without any doubt, the ability to collect raw data and turn it into useful information for workers is essential to staying competitive.
But what if you’re unsure of how to bring analytics to your operations?
Where are you if the goal is to deploy analytics, but no defined strategy is in place?
Fortunately, implementing analytics doesn’t have to be a mysterious or
overwhelming task.

What’s the best way to start learning machine learning in Python?

Automated feature engineering with featuretools is a complicated concept built on simple ideas.
Using concepts of entitysets, entities, and relationships, featuretools can perform deep feature synthesis to create new features.
Deep feature synthesis in turn stacks feature primitives — aggregations, which act across a one-to-many relationship between tables, and transformations, functions applied to one or more columns in a single table — to build new features from multiple tables.