Machine learning is the field of study that allows computers to learn without being explicitly programmed. It has many real-world applications including image recognition, speech recognition, product recommendations, self-driving cars, and automatic language translation. There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning involves giving the program labeled input data and expected outputs to train on, while unsupervised learning does not use labeled data.
2. What is Machine
Learning?
Machine learning is defined as the “Field of study that gives
computers the capability to learn without being explicitly
programmed”.
3. Applications of Machine
Learning
We are using machine learning in our daily life even without knowing it
such as Google Maps, Google assistant, Alexa, etc.
Below are some most trending real-world applications of Machine
Learning:
1. Image Recognition
2. Speech Recognition
3. Product recommendations
4. Self-driving cars
5. Virtual Personal Assistant
6. Automatic Language Translation
5. Supervised Learning
Supervised learning is an approach where the program is given
labeled input data and the expected output. "Supervised learning
is a technique in which we teach or train the machine using data
which is well labeled".
6. Types of Supervised
Learning
Classification - Classification algorithms are used to predict or
classify items into discrete valued groups such as Male or Female,
True or False, Spam or Not Spam, etc.
Regression - Regression tasks are different, as they expect
the model to predict continuous data.
7. Steps to follow:-
● Gathering data
● Data Preprocessing
● Training the data
● Evaluation
8. Linear Regression
Linear Regression is the most basic algorithm in Machine Learning. It
is a regression algorithm, which means that it is useful when we are
required to predict continuous values, that is, the output variable
‘y’ is continuous in nature.
9. A few examples of the regression problem can be the
following
1. “What is the market value of the house?”
2. “Stock price prediction”
3. “Sales of a shop”
4. “Predicting height of a person”
Application of Linear
Regression
