From d0578d77c7bc8399bc3b78168d4f68e09ce0d097 Mon Sep 17 00:00:00 2001 From: rasbt Date: Thu, 15 Dec 2016 21:55:38 -0500 Subject: [PATCH] ai and ml faq --- README.md | 1 + faq/README.md | 1 + faq/ai-and-ml.md | 13 +++++++++++++ faq/ai-and-ml/ai-and-ml-1.png | Bin 0 -> 89423 bytes 4 files changed, 15 insertions(+) create mode 100644 faq/ai-and-ml.md create mode 100644 faq/ai-and-ml/ai-and-ml-1.png diff --git a/README.md b/README.md index e6e0b4e5..d5eaaf33 100644 --- a/README.md +++ b/README.md @@ -238,6 +238,7 @@ starting to gather some of these great applications, and I'd be more than happy ### Questions about the Machine Learning Field +- [How are Artificial Intelligence and Machine Learning related?](./faq/ai-and-ml.md) - [What are some real-world examples of applications of machine learning in the field?](./faq/ml-examples.md) - [What are the different fields of study in data mining?](./faq/datamining-overview.md) - [What are differences in research nature between the two fields: machine learning & data mining?](./faq/datamining-vs-ml.md) diff --git a/faq/README.md b/faq/README.md index 23d27d8a..d10decfc 100644 --- a/faq/README.md +++ b/faq/README.md @@ -35,6 +35,7 @@ Sebastian ### Questions about the Machine Learning Field +- [How are Artificial Intelligence and Machine Learning related?](./ai-and-ml.md) - [What are some real-world examples of applications of machine learning in the field?](./ml-examples.md) - [What are the different fields of study in data mining?](./datamining-overview.md) - [What are differences in research nature between the two fields: machine learning & data mining?](./datamining-vs-ml.md) diff --git a/faq/ai-and-ml.md b/faq/ai-and-ml.md new file mode 100644 index 00000000..fe2129d7 --- /dev/null +++ b/faq/ai-and-ml.md @@ -0,0 +1,13 @@ +# How are Artificial Intelligence and Machine Learning related? + +Artifical Intellicence (AI) started as a subfield of computer science with the focus on solving tasks that humans can but computers can't do (for instance, image recognition). AI can be approached in many ways, for example, writing a computer program that implements a set of rules devised by domain experts. Now, hand-crafting rules can be very labrorious and time consuming. + +The field of machine learning -- originally, we can consider it as a subfield of AI -- was concerned with the development of algorithms so that computers can automatically learn (predictive) models from data. + +For instance, say we want to develop a program that can recognize handwritten digits from images. One would be to look at all of these images and come-up with a set of (nested) if-this-than-that rules to say which image is displayed in a particular image (for instance, by looking at the relative locations of pixels). Another approach would be to use a machine learning algorithm, which can fit a predictive model based on a thousands of labeled image samples that we may have collected in a database. Now, there's also deep learning, which in turn is a subfield of machine learning, referring to a particular subset of models that are particularly good at certain tasks such as image recognition and natural language processing. + +Or in short, machine learning (and deep learning) definitely helps to develop "AI," however, AI doesn't necessarily have to be developed using machine learning -- although, machine learning makes "AI" much more convenient ;). + +tldr; to summarize my point of view visually: + +![](ai-and-ml/ai-and-ml-1.png) diff --git a/faq/ai-and-ml/ai-and-ml-1.png b/faq/ai-and-ml/ai-and-ml-1.png new file mode 100644 index 0000000000000000000000000000000000000000..1368369ddf24332df8373ecd1015eadd73fab89a GIT binary patch literal 89423 zcmeGE30gS)!~w;+Ka2?Plm+}(q_2e;r2oc^t~ z_kPyA1$k)=I5-3eI5+?w2nm*A zc&Szk2M6zOD4)TJ85nF5f;W4Eas68dx23U3jI2TumF*nqE{r98oc zc;aM@_W|DH;_RYZyn|Z;D1aN0qCaDreh6M1CW>JYZ$utqjV9>|p6!+CUhUFY_!Qi# 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