# Category Archives: [MACHINE LEARNING]

# [MACHINE LEARNING] FIN AI, Eminem

A. Background As I am taking the Machine Learning, I wanted to make a machine learning that can generate the rap lyrics. So, I needed the data of the certain rapper. I picked Eminem, because of the article “Eminem Has the

# [MACHINE LEARNING] FIN AI, Eminem

A. Background As I am taking the Machine Learning, I wanted to make a machine learning that can generate the rap lyrics. So, I needed the data of the certain rapper. I picked Eminem, because of the article “Eminem Has the

# [MACHINE LEARNING] WK4,5

I searched on the youtube to find the reasonings to the learning machines because I wanted to understand the theoretical background. I found this biological explanation which shows where the summation Σ function and Sigmoid function came from. Equation of

# [MACHINE LEARNING] WK4,5

I searched on the youtube to find the reasonings to the learning machines because I wanted to understand the theoretical background. I found this biological explanation which shows where the summation Σ function and Sigmoid function came from. Equation of

# [MACHINE LEARNING]WK3 Perceptron

I made an options related to the OR, AND and XOR so that an user can select the function. 1 and -1 were taken as True and False. At the end, I plotted the numbers of output and the graph is

# [MACHINE LEARNING]WK3 Perceptron

I made an options related to the OR, AND and XOR so that an user can select the function. 1 and -1 were taken as True and False. At the end, I plotted the numbers of output and the graph is

# [MACHINE LEARNING]WK2 Recommendation (Euclidean and Pearson)

I made a date recommendation with the python for 2 users. One is based on the Euclidean distance and the other is based on the Pearson correlation. I used numpy and math function to do an array/vector calculations. One was

# [MACHINE LEARNING]WK2 Recommendation (Euclidean and Pearson)

I made a date recommendation with the python for 2 users. One is based on the Euclidean distance and the other is based on the Pearson correlation. I used numpy and math function to do an array/vector calculations. One was

# [MACHINE LEARNING]WK1 Implement Run-length Encoding

Implement Run-length encoding(IRE) in Python. So, I used the array string to make the IRE. In the for loop, in range of 0 to the length of the array, I tried to compare x[i] with x[i+1] which will compare like

# [MACHINE LEARNING]WK1 Implement Run-length Encoding

Implement Run-length encoding(IRE) in Python. So, I used the array string to make the IRE. In the for loop, in range of 0 to the length of the array, I tried to compare x[i] with x[i+1] which will compare like