From 5dabfb2ea442887f83afc51874fd4d4a9981e77b Mon Sep 17 00:00:00 2001 From: Swati Maurya Date: Fri, 10 Sep 2021 11:47:09 +0530 Subject: [PATCH 1/3] SwatiMaurya_ML is added --- SwatiMaurya_ML/Swati_ML.txt | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 SwatiMaurya_ML/Swati_ML.txt diff --git a/SwatiMaurya_ML/Swati_ML.txt b/SwatiMaurya_ML/Swati_ML.txt new file mode 100644 index 000000000..6252b57b3 --- /dev/null +++ b/SwatiMaurya_ML/Swati_ML.txt @@ -0,0 +1,2 @@ +Nowadays, humans can easily grab native things or learn new technologies but if we talk about machines then here a question arises that “Can machines also, learn from their past experience.” +So the answer is “YES”.Machine learning can adopt skills in the absence of human involvement and acquire knowledge. Machine learning is a technology that accredits computers to learn from past experience. Machine learning techniques can be used in various programs like speech recognitions, email filtering, image recognition, recommender system, etc. Machine learning has been categorized as a base class of artificial intelligence. From ce28be9fa3ebeb222265293bb2ea51471eb78d15 Mon Sep 17 00:00:00 2001 From: swati2603 <72228731+swati2603@users.noreply.github.com> Date: Fri, 10 Sep 2021 12:14:43 +0530 Subject: [PATCH 2/3] Update and rename Swati_ML.txt to Swati_ML.md --- SwatiMaurya_ML/Swati_ML.md | 3 +++ SwatiMaurya_ML/Swati_ML.txt | 2 -- 2 files changed, 3 insertions(+), 2 deletions(-) create mode 100644 SwatiMaurya_ML/Swati_ML.md delete mode 100644 SwatiMaurya_ML/Swati_ML.txt diff --git a/SwatiMaurya_ML/Swati_ML.md b/SwatiMaurya_ML/Swati_ML.md new file mode 100644 index 000000000..53ae12059 --- /dev/null +++ b/SwatiMaurya_ML/Swati_ML.md @@ -0,0 +1,3 @@ +# Introduction to Machine Learning +Nowadays, humans can easily grab native things or learn new technologies but if we talk about machines then here a question arises that “Can machines also, learn from their past experience?” +So the answer is “YES”.Machine learning can adopt skills in the absence of human involvement and acquire knowledge. Machine learning is a technology that accredits computers to learn from past experience. Machine learning techniques can be used in various programs like speech recognitions, email filtering, image recognition, recommender system, etc. Machine learning has been categorized as a base class of artificial intelligence. diff --git a/SwatiMaurya_ML/Swati_ML.txt b/SwatiMaurya_ML/Swati_ML.txt deleted file mode 100644 index 6252b57b3..000000000 --- a/SwatiMaurya_ML/Swati_ML.txt +++ /dev/null @@ -1,2 +0,0 @@ -Nowadays, humans can easily grab native things or learn new technologies but if we talk about machines then here a question arises that “Can machines also, learn from their past experience.” -So the answer is “YES”.Machine learning can adopt skills in the absence of human involvement and acquire knowledge. Machine learning is a technology that accredits computers to learn from past experience. Machine learning techniques can be used in various programs like speech recognitions, email filtering, image recognition, recommender system, etc. Machine learning has been categorized as a base class of artificial intelligence. From 49909d40f6ee9ec03015f9404080a7d87368dbc0 Mon Sep 17 00:00:00 2001 From: swati2603 <72228731+swati2603@users.noreply.github.com> Date: Fri, 10 Sep 2021 23:30:04 +0530 Subject: [PATCH 3/3] Update Swati_ML.md --- SwatiMaurya_ML/Swati_ML.md | 25 ++++++++++++++++++++++++- 1 file changed, 24 insertions(+), 1 deletion(-) diff --git a/SwatiMaurya_ML/Swati_ML.md b/SwatiMaurya_ML/Swati_ML.md index 53ae12059..455480526 100644 --- a/SwatiMaurya_ML/Swati_ML.md +++ b/SwatiMaurya_ML/Swati_ML.md @@ -1,3 +1,26 @@ # Introduction to Machine Learning Nowadays, humans can easily grab native things or learn new technologies but if we talk about machines then here a question arises that “Can machines also, learn from their past experience?” -So the answer is “YES”.Machine learning can adopt skills in the absence of human involvement and acquire knowledge. Machine learning is a technology that accredits computers to learn from past experience. Machine learning techniques can be used in various programs like speech recognitions, email filtering, image recognition, recommender system, etc. Machine learning has been categorized as a base class of artificial intelligence. +So the answer is “YES”. Machine learning can adopt skills in the absence of human involvement and acquire knowledge. Machine learning is a technology that accredits computers to learn from past experience. Machine learning techniques can be used in various programs like speech recognitions, email filtering, image recognition, recommender system, etc. Machine learning has been categorized as a base class of artificial intelligence. + +# Supervised and Unsupervised Learning +These two techniques come under the category of machine learning. Both techniques help to deal with different datasets in different situations. +### 1. Supervised Learning +* Supervised learning algorithms are trained using labeled data. +* In supervised learning, input data is provided to the model along with the output. +* A Supervised learning model predicts the output. +* Supervised learning can be categorized into Classification and Regression problems. +### 2. Unsupervised Learning +* Unsupervised learning algorithms are trained using unlabeled data. +* In unsupervised learning, only input data is provided to the model. +* An Unsupervised learning model finds the hidden patterns in data. +* Unsupervised Learning can be classified as Clustering and Associations problems. + +## Now let's understand What is Linear regression? +Whenever we are dealing with prediction problems we prefer to use the Linear Regression algorithm. It makes predictions for continuous/real or numeric variables such as prices, sales, age, etc. Linear regression algorithm presents a linear relationship between a dependent and (Y) and one or more independent variables(X), hence called linear regression. + +### There are two types of Linear regression: +1. Simple Linear Regression: +If a single independent variable is used to predict the value of a numerical dependent variable, then such a Linear Regression algorithm is called Simple Linear Regression. +2. Multiple Linear regression: +If more than one independent variable is used to predict the value of a numerical dependent variable, then such a Linear Regression algorithm is called Multiple Linear Regression. +