Machine learning: Difference between revisions
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Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look. <ref> https://www.sas.com/en_us/insights/analytics/machine-learning.html </ref> This is important to our case study as it allows self-driving cars to learn from it’s environment and mistakes. | Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look. <ref> https://www.sas.com/en_us/insights/analytics/machine-learning.html </ref> This is important to our case study as it allows self-driving cars to learn from it’s environment and mistakes. | ||
== | == Terminology == | ||
# [[Behavioural data]] | |||
# [[Cloud delivery models:]] | |||
# [[Infrastructure as a service (IaaS)]] | |||
# [[Platform as a service (PaaS)]] | |||
# [[Software as a service (SaaS)]] | |||
# [[Cloud deployment models]] | |||
# [[Collaborative filtering]] | |||
# [[Content-based filtering]] | |||
# [[Cost function]] | |||
# [[F-measure]] | |||
# [[Hyperparameter]] | |||
# [[K-nearest neighbour (k-NN) algorithm]] | |||
# [[Matrix factorization]] | |||
# [[Mean absolute error (MAE)]] | |||
# [[Overfitting]] | |||
# [[Popularity bias]] | |||
# [[Precision]] | |||
# [[Recall]] | |||
# [[Reinforcement learning]] | |||
# [[Right to anonymity]] | |||
# [[Right to privacy]] | |||
# [[Root-mean-square error (RMSE)]] | |||
# [[Stochastic gradient descent]] | |||
# [[Training data]] | |||
== Examples == | == Examples == | ||
Revision as of 08:58, 8 June 2022
Introduction[edit]
Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look. [2] This is important to our case study as it allows self-driving cars to learn from it’s environment and mistakes.
Terminology[edit]
- Behavioural data
- Cloud delivery models:
- Infrastructure as a service (IaaS)
- Platform as a service (PaaS)
- Software as a service (SaaS)
- Cloud deployment models
- Collaborative filtering
- Content-based filtering
- Cost function
- F-measure
- Hyperparameter
- K-nearest neighbour (k-NN) algorithm
- Matrix factorization
- Mean absolute error (MAE)
- Overfitting
- Popularity bias
- Precision
- Recall
- Reinforcement learning
- Right to anonymity
- Right to privacy
- Root-mean-square error (RMSE)
- Stochastic gradient descent
- Training data
Examples[edit]
An excellent, and I truly mean excellent example is MarI/O, a machine learning program that learns how to play mario, and mario kart.
Super Mario World: https://www.youtube.com/watch?v=qv6UVOQ0F44
Mario Kart: https://www.youtube.com/watch?v=S9Y_I9vY8Qw
[3]