In this section, which is the first part of the chapter from the Python programming course, we start together.
In the following, we are going to learn a good part of machine learning and the main part of this course is supervice learning and we will deal with unsupervice learning a bit.
The order of the sections of this course will be as follows, which will be added during the course:
- Numpy
- Pandas
- Matplotlib & Searbon
- Linear Regression
- Logistic Regression (Comes with "Multi_Regression")
- Preprocessing (With scikit-learn library)
- GridSerach & Cross-Validatoin
- Regularization
- K-Nearest Neighbor
- Naive_Bayes
- Artificial Neural Network
- Support Vector Machine (SVM)
- Support Vector Regression (SVR)
- Decision Tree (Regression & Classification)
- Random Forest (Regression & Classification)
- XGBoost (Regression & Classification)
- k_means
- DBScan
- Principal Component Analysis (PCA)
- Streamlit App
- PyCaret
- Projects
be happy :)