Remove Deep Learning Remove Predictive Analytics Remove Visualization
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Rapidminer Platform Supports Entire Data Science Lifecycle

David Menninger's Analyst Perspectives

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. Rapidminer Studio is its visual workflow designer for the creation of predictive models.

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Predictive Analytics: 4 Primary Aspects of Predictive Analytics

Smart Data Collective

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

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Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

It can be used for something as visual as reducing traffic jams, to personalizing products and services, to improving the experience in multiplayer video games. This is something that you can learn more about in just about any technology blog. We would like to talk about data visualization and its role in the big data movement.

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Top 14 Must-Read Data Science Books You Need On Your Desk

datapine

We gave you a curated list of our top 15 data analytics books , top 18 data visualization books , top 16 SQL books – and, as promised, we’re going to tell you all about the world’s best books on data science. 2) “Deep Learning” by Ian Goodfellow, Yoshua Bengio and Aaron Courville. click for book source**.

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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

But heres the question I keep asking myself: do we really need this immense power for most of our analytics? Think about it: LLMs like GPT-3 are incredibly complex deep learning models trained on massive datasets. In analytics, LLMs can create natural language query interfaces, allowing us to ask questions in plain English.

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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. Whether the company needs a comprehensive financial analytics strategy or process, R has become one of the most used data science tools to explore and manage data. Let’s get started.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

Diagnostic analytics uses data (often generated via descriptive analytics) to discover the factors or reasons for past performance. Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes.