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Machine Learning
Machine learning is an application of Artificial Intelligence (AI) that enables systems to learn and improve automatically
from experience without the need for explicit programming. It focuses on the development of computer programs
that can access data and use it to learn for itself. Data is critical for machine learning to work. The more data the
machine is given (assuming that this data is reliable), the more accurate is its prediction.
Artificial
Intelligence Intelligent machines that think
and act like human beings
Machine Systems learn things without
Learning being programmed to do so
Machine Learning Process
Machine Leaning follows a process which is displayed in the following diagram:
1. Preparing data
Machine Learning Process 3. Generating a set of instructions (the model)
2. Training an algorithm
4. Using features to make and refine predictions
until the model can accurately make predictions
on new input data
Features of Machine Learning
Following are the features of Machine Learning:
• It is the science of having machines interpret, analyse and process data as a way to fix real-world problems.
• It learns from data and improve over time. These learnings can be used for automation or prediction.
• It is the dominant mode of AI today.
• It uses data analysis, training, and human review to learn without following specific rules or steps.
Conventional Programming Vs Machine Learning
Conventional programming is a manual process—meaning a person (programmer) creates the program. But without
anyone programming the logic, one has to manually formulate or code rules.
Input Program Output
In machine learning, on the other hand, the algorithm automatically formulates the rules from the data. Unlike
traditional programming, machine learning is an automated process.
Input Output Program
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