The field of artificial intelligence and the techniques of machine learning rely on the volume and variety that is inherent in big data and would not exist as we know them without big data.
- [Instructor] When people think … about advanced data work these days, … the mind is immediately drawn … towards artificial intelligence and machine learning … the way that the mind was automatically drawn … towards big data a few years ago. … But to understand the connection … between big data and these other fields, … because there is a connection, … it's worth reminding ourselves about what they all mean. … So for instance, artificial intelligence … is a field in data science and in computer science … and it's the field that focuses on techniques … that allow computers to do things typically done by humans … like play a game of Go or classify photos, … or evaluate MRIs, and it's usually done in a way … that shows adaptability to new circumstances … or it shows intelligence and flexibility … in responding to the data that's coming in. … Machine learning, on the other end, … is a collection, a rubric of algorithms … that can find patterns in data to predict outcomes … like, for instance, whose face is this …
Author
Barton Poulson
Released
9/19/2019- Identify the components that make up big data.
- Examine how big data has grown over the last few years.
- Explain the importance of using big data in business organizations.
- Distinguish between knowledge requirements for using big data and for understanding data science.
- Justify the need for training on big data within an organization.
- Analyze the factors that go into utilizing big data on a project.
- Differentiate outcomes that are derived from big data from outcomes that are derived from observing behaviors.
Skill Level Beginner
Duration
Views
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Introduction
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How big data shapes AI1m 46s
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1. Defining Big Data
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2. How Is Big Data Used?
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Big data for applications4m 41s
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3. Big Data and Data Science
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4. Ethics in Big Data
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Big data and privacy5m 52s
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Data governance6m 2s
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5. Data Logistics
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An evolving data landscape5m 48s
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6. Analyzing Big Data
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Visualizing big data5m 13s
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Data mining4m 39s
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Text analytics4m 18s
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Sentiment analysis4m 48s
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Predictive analytics4m 7s
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Anomaly detection3m 59s
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Conclusion
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Next steps2m 56s
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Video: Artificial intelligence and machine learning