With the rise of Chat-GPT by OpenAI, the topic of ‘Will my job be replaced?’ has risen, and it becomes a concern that many are talking about today.
This topic seems terrifying despite that AI now can only serve as an aid to humans, but we never know where it will go in a few years. To me, the answer will always be “instead of being afraid of a trend, join the trend instead”.
Artificial Intelligence (AI) is a broad term. Machine Learning and Deep Learning are considered to make up the majority of the term “AI” that many are talking about today, and Deep Learning can be classified under Machine Learning.
The main application of Machine Learning is to make predictions of the future from past data. In other words, the machine is capable of finding out the patterns within data, and patterns in the data that lead to a certain outcome, thus, predicting the future.
In this series of articles, I will be explaining the applications of Machine Learning and some of the theories behind it. The topics that I will be covering are:
1. Data Preprocessing
2. ML Algorithms
Regression
a. Linear Regression
b. Polynomial Regression
c. Support Vector Regression (SVR)
d. Decision Tree Regression
e. Random Forest RegressionClassification
a. Logistic Regression
b. K-Nearest Neighbours (KNN)
c. Support Vector Machine (SVM)
d. Kernel SVM
e. Naive Bayes
f. Decision Tree Classification
g. Random Forest Classification
> Continue reading: Data Preprocessing
