What is Machine learning: Definition and 82 Discussions

Machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.A subset of machine learning is closely related to computational statistics, which focuses on making predictions using computers; but not all machine learning is statistical learning. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a related field of study, focusing on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is also referred to as predictive analytics.

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  1. J

    Python Why backpropagation dominates neural networks instead of interpolation

    Hi guys, I was learning machine learning and I found something a bit confusing. When I studied physics I saw the method of least squares to find the best parameters for the given data, in this case we assume we know the equation and we just minimize the error. So if it is a straight line model...
  2. mhr005

    Software to Simulate a Renewable Grid with ML

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  3. R

    Physics Does a datascience job help in applying for PhD or physics scholarship

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  4. N

    What is the goal of the problem?

    Question: Correct Answer: U and VT in code:
  5. D

    ROC Curve: Background Rejection vs. Signal Efficiency

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  6. A

    Can AI Technologies Interpret and Convert Musical Notes into Audio?

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  7. A

    New Olympic games Logo Designs -- Can Machine Learning help?

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  8. M

    Machine learning with image tracking of a line

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  9. Wrichik Basu

    Courses Which of these Machine Learning courses should I attend?

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  10. B

    Python Forecasting Bitcoin (BTC) with Machine Learning

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  11. Mikkel

    Deep Learning for Image Recognition in Astrophysics

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  12. A

    Tracing correct words from Jumbled words using machine learning

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  13. W

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  14. Frabjous

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  15. E

    Programs I chose math instead of physics. Was it a mistake?

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  16. gleem

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  17. Phylosopher

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  18. hdp12

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  19. R

    Can machine learning be used to treat diseases?

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  20. D

    A Applications of analysis in signal processing/machine learning?

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  21. Y

    Machine Learning - Empirical Error

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  22. F

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  23. A

    Studying Self-studying plan for modern science

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  24. L

    Resource recommendations for machine learning

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  25. F

    Machine learning vs statistics

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  26. D

    Programs Diploma thesis - Neural Network Application in Physical Problems

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  27. A

    Python How to get output from a layer during training in Keras?

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  28. J

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  29. R

    Math Job opportunities USA that combine data science with physics

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  31. ngrunenberg

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  33. Felipe Lincoln

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  34. P

    A Recently, I want to write something about data in physics

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  35. M

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  36. G

    Prob/Stats Books on Machine Learning without a strong math background required

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  37. Curiose

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  38. P

    Mind boggling machine learning results from AlphaZero

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  39. E

    Good books to learn machine learning using Python

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  40. It's me

    I How can I access event data for LHCb calorimeters?

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  41. Q

    Physics Machine learning with particle physics

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  42. jedishrfu

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  43. V

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  44. Q

    Admissions Computational physics career change

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  45. C

    Machine learning / AI - Where do I start?

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  46. K

    Applied Differential geometry for Machine Learning

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  47. Gean Martins

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  48. Ackbach

    MHB Fantastic Machine Learning Course

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  49. FallenApple

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    From what I understand, machine learning is incredibly good at making predictions from data in a very automated/algorithmic way. But for any inference that is going to deal with ideas of causality, it's primarily a subject matter concern, which relies on mostly on judgment calls and intuition...
  50. G

    B Machine learning + Kepler data

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