Chapter 1: Introduction to Machine Learning

Question 1

Types of Machine Learning?

Answer 1

Supervised and Unsupervised learning

Question 2

What is Supervized Machine Learning?

Answer 2

1. Uses labeled datasets to train.
2. Contains examples of both inputs (called features) and correct outputs (labels).

Question 3

Types of Supervized Machine Learning?

Answer 3

1. Classification
2. Regression

Question 4

What are the problems of the Supervized Machine Learning Technique?

Answer 4

1. Bias-variance dilemma: how the ML model performs accurately using different training sets?
2. High-bias models: how to deal with complex and noisy training dataset?
3. Size of the training dataset: what is the acceptable size of the training dataset for the ML algorithm to compute accurate classification and prediction?

Question 5

What is Unsupervized Machine Learning?

Answer 5

1. Learns from data without human supervision.
2. Models are given unlabeled data and allowed to discover patterns and insights without any explicit guidance or instruction

Question 6

Types of Unsupervized Machine Learning?

Answer 6

1. Clustering
2. Association
3. Dimensionality reduction

Question 7

Where can ML be applied in real life?

Answer 7

1. Spam detection
2. Voice recognition
3. Stock trading
4. Robotics
5. E-commerce

Question 8

Types of Machine Leaning Languages?

Answer 8

1. Python
2. R
3. Matlab
4. Scala-Scalable language
5. Ruby

Question 9

Types of ML Software?

Answer 9

1. WEKA (Open source)
2. KafKa
3. Spark & Hadoop
4. DeepLearning4J