Chapter 2 - What is Machine Learning?

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Machine learning is a branch of:

Artificial Intelligence and computer science

How does the decision process work?

Based on some input, which can be labeled or unlabelled, the algorithm will produce an estimate about the pattern in the data.

How does the error function work?

By making a comparison to assess the accuracy of the model.

How does the model optimization process work?

By making a process of evaluating and optimizing the model automatically, until a threshold of accuracy has been met.

Definition of supervised machine learning:

Models are trained with labeled data sets, which allow the model to learn and grow and be accurate over time.

A 2020 Deloitte survey found.

That 67% of companies are using machine learning, and 97% are planning to use it next year.

Definition of unsupervised machine learning:

a program that look for patterns in unlabeled data sets. The program can find trends or patterns that people aren't explicitly looking for.

Definition of Machine Learning:

is the field of building algorithms that can learn patterns by themselves without being programmed explicitly

How does Machine Learning work?

1. Decision Process 2. An Error Function 3. Model Optimization Process

What are the functions of machine learning?

1. Descriptive 2. Predictive 3. Prescriptive

What is the machine learning process?

1. Identifies relevant data sets and prepare them for analysis 2. Choose the type of machine learning algorithm to use. 3. Build an analytical model. 4. Train the model on the test data set. 5. Run the model to generate findings.

Why is machine learning important?

1. It gives a view of trends in customer behavior and business operational patterns. 2. It supports the development of new products.

The types of machine learning:

1. Supervised machine learning 2. Unsupervised machine learning 3. Reinforcement machine learning

Definition of a prescriptive system:

The system use data to make suggestion about what actions to take.

Definition of a descriptive system:

The system uses data to explain what happened.

Definition of a predictive system:

The system uses data to explain what will happen.

Definition of reinforcement machine learning:

Trains machines through trial and error to take the best actions by establishing a reward system.


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