Machine Learning

https://www.geeksforgeeks.org/machine-learning/machine-learning-models/

https://www.geeksforgeeks.org/supervised-machine-learning/

https://www.geeksforgeeks.org/machine-learning/unsupervised-learning/

https://www.geeksforgeeks.org/machine-learning/what-is-reinforcement-learning/

https://www.geeksforgeeks.org/machine-learning/ml-semi-supervised-learning/

https://www.geeksforgeeks.org/machine-learning/self-supervised-learning-ssl/

https://www.geeksforgeeks.org/machine-learning/python-image-classification-using-keras/

Berikut adalah beberapa algoritma supervised learning yang penting Anda ketahui, dan akan dibahas di kelas Belajar Machine Learning untuk Pemula:

Linear Regression
Logistic Regression
Classification
Decision Trees
Support Vector Machines
Neural Networks.

from google.colab import files

uploaded = files.upload()

import pandas as pd

Membaca file iris.csv

iris = pd.read_csv('Iris.csv')

import pandas as pd

import io

df = pd.read_csv(io.BytesIO(uploaded['YOUR_FILE_NAME.csv']))

print(df)

Classification

https://www.kaggle.com/datasets/uciml/iris?resource=download

Practice:

https://colab.research.google.com/drive/1ZMJbDrrICh08Inqxi22co_5JnEXCxuox?usp=sharing

Linear Regression

https://colab.research.google.com/drive/1ZlDUw8i2r5M6TZ-95RZ5mpGPQTb38uMw?usp=sharing

Latihan SKLearn Logistic Regression

https://colab.research.google.com/drive/1HNVdUUVD94GhFCvSkw3vua7YuHcJhIfw?usp=sharing

Unsupervised Learning

Beberapa algoritma unsupervised learning yang penting untuk Anda ketahui adalah: clustering, dimensionality reduction, anomaly detection, dan density estimation.

Sklearn K-means Clustering.ipynb

https://colab.research.google.com/drive/1x9M1VsVnNGnUqdxkqJcYSpWUZVFlx7Sr?usp=sharing

Linear Discriminant Analysis

https://sebastianraschka.com/Articles/2014_python_lda.html

1.2. Linear and Quadratic Discriminant Analysis¶

https://scikit-learn.org/stable/modules/lda_qda.html

An illustrated introduction to the t-SNE algorithm

https://www.oreilly.com/content/an-illustrated-introduction-to-the-t-sne-algorithm/

https://lvdmaaten.github.io/tsne/

https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html

SKLearn PCA

https://colab.research.google.com/drive/12jGV3s8xHxF-GOgcEFzjG2uCasEd5hfN?usp=sharing

Berikut adalah beberapa fungsi kernel yang perlu Anda ketahui.

Linear
RBF (Radial Basis Function) atau Gaussian kernel
Polinomial
Sigmoid

Tertarik mengetahui fungsi matematis di balik kernel? Kunjungi tautan berikut yah.

Latihan SKLearn SVM untuk Klasifikasi

https://colab.research.google.com/drive/1IrVEmBvVWfXnhyD0xcQQ0p6kvK16yNgy?usp=sharing

Latihan SKLearn SVR

https://colab.research.google.com/drive/1FR_R6ERR5RNeE4B_37za_GhNqko2CqEG?usp=sharing

Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits.pdf

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