ML Practice 8_2
Prepare Fashion Mnist Data12345678from tensorflow import kerasfrom sklearn.model_selection import train_test_split(train_input, train_target), (test_input, test_target) =\ keras.datasets.fashion_mnis
Category: python
ML Practice 8_1
CNN(Convolution Neural Network) Neural network operations can also be applied to two-dimensional arrays by CNN. Neuron in CNN is called filter or kernel. 12from tensorflow import keraskeras.layers.Co
Pipeline Tutorial
Pipeline : 데이터 누수(Data Leakge) 방지를 위한 모델링 기법 Pycaret, MLOps (Pipeline 형태로 구축) 머신러닝 코드의 자동화 및 운영 가능 기존 방식 데이터 불러오기 -> 데이터 전처리 -> 특성 공학 -> 데이터셋 분리 -> 모델링 -> 평가 파이프라인 방식 데이터 불러오기 ->
ML Practice 7_3
Create DNN Model12345678910from tensorflow import kerasfrom sklearn.model_selection import train_test_split(train_input, train_target), (test_input, test_target) = \ keras.datasets.fashion_mnist.lo
ML Practice 7_2
Prepare Dataset123from tensorflow import keras(train_input, train_target), (test_input, test_target) = keras.datasets.fashion_mnist.load_data() 1234567from sklearn.model_selection import train_test_
ML Practice 7_1
Fashion MNISTDeep Learning Library tensorflow : https://www.tensorflow.org/ pytorch : https://pytorch.org/ 12import tensorflowprint(tensorflow.__version__) 2.8.0 Load Data12from tensorflow import k
ML Practice 6_3
Dimensionaliy Reduction: Decreasing the size of the data by selecting some features that best represent the data To prevent overfitting and improve model performance PCA(Principal Component Analysis),
ML Practice 6_2
K-means Clustering Find mean of pixel value : cluster center, centroid Determine the centers of k clusters at random. Find the nearest cluster center from each sample and designate it as a sample of t
ML Practice 6_1
Unsupervised Learning No dependent variables and targets. (↔ Supervised Learning) Clustering (Multiple class) Must be many different types of data Linked to deep learning Dimensionality reduction I
ML Practice Tree plot Example
Goal : To change the color of tree plot1!pip install -U matplotlib Requirement already satisfied: matplotlib in c:\programdata\anaconda3\lib\site-packages (3.4.3) Collecting matplotlib Downloading