In this repo, there are projects and homework that is given by the instructors. This course is provided by "Kodluyoruz" and "Carbon Consulting".
- Meeting and Syllabus check.
- What is AI?
- Numpy, Pandas, Sklearn, Seaborn, Matplotlib libraries
- Exploratory Data Analysis
- Data collection, labeling and save (Web Scraping)
- Supervised, Unsupervised Training Methods
- Linear and Logistic Regression
- Decision Tree and Random Forest
- Titanic Project
- Clustering, KNN, DBScan
- Dimensionality Reduction
- Clustering Project
- Introduction to Neural Networks, Loss, Activation and Optimizer
- Keras, TensorFlow, PyTorch libraries
- Classification and Regression with Keras
- RNN, LSTM
- Introduction to NLP
- NLP Project
- Bonus: Docker
- CNN
- Image Processing
- Image Processing Project
import Pandas
import Numpy
import Seaborn
import Matplotlib
import Sklearn
import statsmodel
import BeautifulSoup
import request
import cv2
import numpy as np
from math import ceil
from scipy.misc import face
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.