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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

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The most valuable AI use cases for business

IBM Big Data Hub

Financial services AI-powered FinOps (Finance + DevOps) helps financial institutions operationalize data-driven cloud spend decisions to safely balance cost and performance in order to minimize alert fatigue and wasted budget. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs. And with advanced software like IBM Watson Assistant , social media data is more powerful than ever.

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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. Source: mathworks.com.