Integrative Programming 3

Question 1

Machine Learning

Answer 1

is a subfield of Artificial Intelligence (AI) that involves the development of algorithms and statistical models that enable computers to learn from and make predictions or take actions based on data.

Question 2

Goal of Machine Learning

Answer 2

is to build systems that can automatically improve their performance with experience, without being explicitly programmed to do so.

Question 3

Types of Machine Learning

Answer 3

1. Supervised Learning
2. Unsupervised Learning
3. Reinforcement Learning

Question 4

Supervised Learning

Answer 4

• the algorithm is trained on labeled data, where the desired output is already known.
• The algorithm then makes predictions on new, unseen data based on the patterns it learned from the labeled data.
• used in applications such as image classification, speech recognition, and regression analysis.

Question 5

Examples of Supervised Learning

Answer 5

• medical daignosis
• credit risk assessment
• studentn record

Question 6

Supervised learning used in

Answer 6

• image classification
• speech recognition
• regression analysis

Question 7

Unsupervised Learning

Answer 7

• algorithm is trained on unlabeled data and must find patterns or structure in the data on its own.
• algorithm does not have a specific target to predict, and the goal is to discover hidden structures or relationships in the data.
• used in applications such as dimensionality reduction, anomaly detection, and clustering.

Question 8

Unsupervised Learning used in

Answer 8

• dimensionality reduction
• anomaly detection
• clustering

Question 9

Examples of Unsupervised Learning

Answer 9

1. image data
2. text data
3. audio data
4. sensor data
5. financial data
6. genome data

Question 10

Reinforcement Learning

Answer 10

• algorithm learns to make decisions in an environment by performing actions and observing the results, with the aim of maximizing a reward signal.
• used in applications such as game playing, robotics, and autonomous systems

Question 11

Reinforcement learning used in

Answer 11

• game playing
• robotics
• autonomous learning

Question 12

How Machine Learning Works

Answer 12

1. algorithm
2. dataset
3. unified data and algorithm (ML models) to satisfy the purpose

Question 13

Steps on how to create Machine Learning

Answer 13

1. define the problem
2. gather the data
3. prepare the data
4. select a model and trainig algorithm
5. test the model
6. evaluate the model
7. fine-tuning the model
8. perform its purpose

Question 14

Things machine learning can do

Answer 14

1. forecast
   2.prediction
   3.categorize
   4.organize
   5.detect

Question 15

Real world application of Machine Learning

Answer 15

1. Image Recognition
2. Natural Language Processing
3. Fraud Detection
4. Recommendation System
5. Predictive Maintenance
6. Healthcare
7. Finance
8. Marketing
9. Customer Service