Machine learning and Deep learning
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Machine learning and Deep learning
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Predictive analytics enables individuals, companies, public institutions and many other organizations to gain valuable insights from their vast collections of data to improve their operations and bring benefits to its customers.
Predictive analytics is the process of mining data and using algorithms to discover the insights and relationships within it. For example, you could have a database of sales transactions over time to analyze what time of day people buy more products, or use concepts from game theory, such as Nash equilibrium, to model the behavior of multiple companies in an industry. The goal is to find patterns and uses within these trends that can help your company in its decision making or to further its business. =)
With all of the buzz around data science and smart algorithms, it’s easy to get lost if you don’t have a foundation. At the same time, there are lots of ways you can use predictive analytics right now. This page is here to provide you with a high-level overview of what predictive analytics is and how you can use it for yourself. It's easier than you think!
Predictive analytics is all about improving customer experience and increasing customer lifetime value. But what's the real difference between a customer and a prospect? Why is it important to know who they are and what they're doing on your website? You can't improve something you don't measure, after all. In this channel, we'll go over how to use predictive analytics to define who your customers really are, in order to maximize your marketing efforts.
With all the excitement about machine learning and artificial intelligence, it’s easy to forget that predictive analytics is still a very powerful tool for businesses. Perhaps you’re wondering whether predictive analytics can really be used for marketing and sales.
These predictive analytics models can be simple statistical models built on data extracted from transactional databases, or they might be advanced algorithmic solutions based on machine learning and AI technologies. However, all of them promote increased sales/profitability, reduced fraud, and greater customer satisfaction if implemented and monitored properly.
Predictive data analytics (or predictive modeling) is the art of creating statistical models (algorithms) to detect patterns and make predictions about the future performance of a business, its customers or its products. Predictive analysis is a tool you can use to improve your marketing, customer service and sales operations, turning it into a strategic driver of growth.
Data science is defined as “a set of skills and techniques” that help us “understand and extract value from data”. Data science strives to answer questions like: how can data help us make better decisions? Is there a pattern in the data? Or how can we create artificial intelligence systems that solve real world problems?
I was blown away upon first seeing a neural style transfer in action. The ability to take an image and apply the brushwork of a great artist onto it is something I never thought I’d be able to do. Neural style transfer provides a compelling way to create a new piece of art that is both visually appealing and novel, which allows people like me to come up with creative ways to generate unique pieces.
Neural style transfer (aka. deep artistic style transfer) is an optimization technique used to take three images, a content image, a style reference image (such as an artwork by a famous painter), and the input image you want to style — and blend them together such that the input image is transformed to look like the content image, but “painted” in the style of the style image.