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Machine Learning Glossary

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Machine Learning Glossary

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AI, Machine Learning & Data: What Businesses Need to Know!

From autonomous driving to predictive analytics, robotic manufacturing to smart homes, how we live, work and play is impacted in profound ways.

CloudFactory makes it super EASY to offload data work so our customers can focus on innovation and growth. We specialize in preparing and organizing data sets and work with companies like Microsoft, Embark, Drive.ai, FaceTec to implement them into building innovative AI, ML and other complex technologies.

AI, Machine Learning & Data: What Businesses Need to Know!

From autonomous driving to predictive analytics, robotic manufacturing to smart homes, how we live, work and play is impacted in profound ways.

CloudFactory makes it super EASY to offload data work so our customers can focus on innovation and growth. We specialize in preparing and organizing data sets and work with companies like Microsoft, Embark, Drive.ai, FaceTec to implement them into building innovative AI, ML and other complex technologies.

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Machine Learning Glossary

  1. 1. AI, Machine Learning & Data What Businesses Need to Know
  2. 2. Artificial intelligence and machine learning are at the forefront of technical innovation.
  3. 3. From autonomous driving to predictive analytics, robotic manufacturing to smart homes, how we live, work and play is impacted in profound ways.
  4. 4. As talk of AI and machine learning permeates our world, the benefits for businesses are getting lost in a sea of technical jargon and prognostication by experts from all walks of life.
  5. 5. At the end of the day, data is the fuel for any machine learning algorithm and it’s common for the terms used to describe how that data is used to become confusing.
  6. 6. As folks who love data, machines, and especially people, we decided to put together a helpful guide to machine learning and the terms that businesses should know as they look to navigate this exciting and complex frontier of technological advancement.
  7. 7. Machine Learning 101 A Glossary of Machine Learning Data Terms
  8. 8. Artificial intelligence is building technology that behaves like a human. Self-driving cars, Siri, smart homes, and many other emerging technologies are examples of AI. Artificial Intelligence
  9. 9. Machine learning is a subset of AI that uses algorithms to learn from data sets. Using data and algorithms, machine learning technologies make intelligent predictions, similar to that of a human, but at scale. Machine Learning
  10. 10. In machine learning, the framework is developed and data is provided, so that machines can teach themselves what they need to know and understand what to do.
  11. 11. Classification is when a set of data trains a machine to identify certain inputs or observations, and based on those, assign them to certain outputs or categories. Classification
  12. 12. Classification is an example of supervised learning, because it uses a set of labeled data examples and classifies any new data into those sets.
  13. 13. Annotation In the traditional sense, an annotation is when we reference a piece of information back to the original source or to additional, relevant data. In machine learning, it’s very similar.
  14. 14. In order to be able to perform sophisticated functions like understanding and responding to human language and verbal commands, computers need to be able to find patterns and make inferences from the data. This is done by creating annotated examples that are in the background of datasets.
  15. 15. Image Tagging Image tagging is the simple act of identifying objects, categories, or even human gestures to help organize data for ground truth data sets and ongoing machine learning applications.
  16. 16. Facial Recognition Facial recognition has primarily been used for security purposes, but new possibilities in marketing and enhanced UX have made facial recognition an important aspect of machine learning.
  17. 17. Natural Language Processing Natural language processing or NLP is the ability for computers to interact in dialogue with humans, either audibly or through text. NLP machine learning technologies are built to understand and communicate with human languages...think of your favorite chatbot :-)
  18. 18. Communication is one of the most natural functions for humans, so it’s crucial to develop natural language processing in AI. Technologies like Siri, Amazon Echo, and Google Home operate using NLP-based algorithms.
  19. 19. Sentiment Analysis Sentiment analysis, also called opinion mining, is the process of studying words and determining their emotional meaning. In other words, you track what people say about you online and determine if those statements are positive, negative, or neutral.
  20. 20. Landmarking Landmark recognition is the ability for technology to identify a building, physical object or landmark. To do this, technology relies on large amounts of image data and smart algorithms.
  21. 21. Machine learning is revolutionizing how we live, work, play, and interact with the world around us. It holds the potential to augment human capabilities to make us smarter and more productive than ever.
  22. 22. CloudFactory is helping companies by providing human intelligence to create accurate training data sets that improve machine learning algorithms. Whether that’s in the form of annotating images, identifying classifiers, drawing bounding boxes, labeling objects or analyzing text for NLP, we’ve made it super easy to offload that work, by spinning up a WorkStream, which empowers data teams and engineers to focus on innovating the next generation of AI that very well may change the world.
  23. 23. About CloudFactory CloudFactory makes it super EASY to offload data work so our customers can focus on innovation and growth. We specialize in preparing and organizing data sets and work with companies like Microsoft, Embark, Drive.ai, FaceTec to implement them into building innovative AI, ML and other complex technologies. www.cloudfactory.com hello@cloudfactory.com (888) 809-0229 SPIN UP A TEAM NOW!

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