Computer Science 썸네일형 리스트형 [E-01] rock_scissor_papaer classification 미니 프로젝트: 가위바위보 분류기를 만들자. 모듈 import import os import numpy as np import matplotlib.pyplot as plt import tensorflow as tf from tensorflow import keras from PIL import Image import glob data load하기 # data load하기 def load_data(img_path, number_of_data=300): # 가위바위보 이미지 개수 총합에 주의하세요. # 가위 : 0, 바위 : 1, 보 : 2 img_size = 28 color = 3 #이미지 데이터와 라벨(가위 : 0, 바위 : 1, 보 : 2) 데이터를 담을 행렬(matrix) 영역을 생성합니다. imgs.. 더보기 05. Vector dot and cross products Vector dot product and vector length link For multiplying vectors or taking the product, there's actually two ways. One of is the dot product. You signfy the dot product by saying a dot b. They borrowed one of the types of multiplication. This is not a vector, this will be a real scalar. So the dot product, you multiply two vectors and you end up with a scalar value. And let's define the length .. 더보기 04. Subspaces and the basis for a subspace Linear subspaces Subspace of $R \space ^ n$ V is some subsset of vectors, some subset of $R \space ^ n$ . In order for V to be a subspace or a linear subspace of $R \space ^ n$ , This means three things. 📖 Defintion of subspace V contains $\vec {0}$ $\vec {x}$ in V $\longrightarrow$ $c \cdot \vec {x}$ in V (Closure under Multiplication) $\vec {a}, \vec {b}$ in V $\longrightarrow$ $\vec {a} + \ve.. 더보기 03. Linear dependence and independence Linear dependence and independence Ex 1 We call this set linearly dependent set. Linearly dependent means that one of the vector in the set can be represented by some combination of the other vectors in the set. Whichever vector you pick that can be represented by the others, it's not adding any new directionaility or any new information! Ex 2 ❓ Are these linearly independent? ❗ nope! v3 is a .. 더보기 02. Linear combinations and span Linear combination: an expression constructed from a set of terms by multiplying each term by a constant and adding the results. Let's see some examples of linear combinations. There are two vectors which is a=[12] , b=[03] When we scale by some scaling factor and add them, we can get those vectors and it's called a linear combination. ex1) 0⋅a+0⋅b=[00] ✔ zero vector is also a linear combinat.. 더보기 01. Vectors 1. Vector intro for linear algebra Vector has both magnitude and direction. Speed is not a vector. This is considered to be a scalar quantity. If we want it to be a vector, we would also have to specify the direction. Velocity is a vector because it has magnitude and direction. And the interesting thing is that we only care about magnitude & dirrection. We don't necessarily not care where we sta.. 더보기 [F-29] Scikit-Learn Intro¶ Aim Learn basic concept of Recommendation using scikit-learn Contents Recommendation system Similarity Types of Recommendation system Content Based Filtering Collaborative Filtering User base Item base Latent Factor Collaborative Filtering -> matrix factorization # making directory $ mkdir -p ~/aiffel/movie_recommendation Recommendation system¶ Recommendation system: a subclass of informa.. 더보기 [F-28] Information Theory Intro¶ Aim Information Theory Entropy, Cross Entropy, KL divergence contents Information Content Entropy Kullback Leibler Divergence Cross Entropy Loss Decision Tree와 Entropy Information Content¶ Information Theory: the mathematical treatment of the concepts, parameters and rules governing the transmission of messages through communication systems. How can we represent informations? Let's say th.. 더보기 이전 1 ··· 6 7 8 9 10 11 12 다음
