• clrs
• 수리통계학
• 자료구조
• 알고리즘
• 논문 리뷰
• R언어
• cs229
• Introduction to Algorithms
• AI
• 데이터분석
• deep learning
• 선형대수학
• Linear Algebra
• Algorithms
• db
• C++
• 딥러닝
• R4DS
• 정렬
• web scraping
• 시간복잡도
• graph
• 파이썬
• introduction to algoritmhs
• 백준
• Machine Learning
• NLP
• Data Structure
• cs 224n
• LSTM
• Python
• paper review
• 밑시딥1
• 밑바닥부터 시작하는 딥러닝1
• ggplot2
• overfitting
• 논문리뷰
• 힙
• Heap
• 프로그래밍
• database system concepts
• tcga
• 행렬곱
• 코테
• RNN
• ggplot
• reinforcement learning
• dynamic programming
• 머신러닝
• EDA
• 힙정렬
• quicksort
• computer vision
• 퀵정렬
• DP
• MST
• sort
• random vector
• forget gate
• lecture 4
• prim algorithms
• bbst
• 마스터 정리
• introduction to algorithm
• RBTree
• label smoothing
• negative sampling
• layer normalization
• 분할 정복
• AdaGrad
• Batch Normalization
• loss function
• ReLU
• GoogLeNet
• word2vec
• Master Theorem
• 분할정복
• Supervised Learning
• 이진탐색트리
• Red-Black Tree
• relation
• softmax
• Null space
• Inception
• 컴퓨터 구조
• Glove
• flights
• Instance
• plot
• 심미성
• Schema
• 매개변수
• 증명
• Adam
• 시각화
• 연결리스트
• dropout
• expectation
• CS
• Queue
• SVM
• R
• 포인터
• 스택
• PS
• HTML
• mongodb basic
• 정보 단위
• lecture 5
• dependency parsing
• backpropagation and neural network basics
• word embedding evaluation
• lecture 2
• word vectors and language models
• evaluation methods for unsupervised word embeddings
• glove: global vectors for word representation
• distributed representations of words and phrasesand their compositionality
• hierarchical softmax
• cvow
• efficient estimation of word representations invector space
• wordnet
• intro & word vectors
• inception-resnet-v2
• polynet: a pursuit of structural diversity in very deep networks
• wild residual network
• aggregated residual transformations for deep neural networks
• xception- deep learning with depthwise separable convolutions
• delayed maxpooling
• expand layer
• droppath
• deep networks with stochastic depth
• navigating tree
• beautifulsoup objects
• urlerror
• introduction to beautifulsoup
• transport layer
• carry gate
• transform gate
• highway networks
• exponential moving average
• inception-resnet and the impact of residual connections on learning
• understanding the difficulty of training deep feedforward neural networks
• he intialization
• prelu
• delving deep into rectifiers:surpassing human-level performance on imagenet classification
• when does label smoothing help?
• going deeper with convolutions
• declarative query language
• functional query language
• imperative query language
• relational query languages
• schema diagrams
• n-tuple
• relation instance
• structure of relational databases
• database system concepts 7th
• database engine
• very deep convolutional networksfor large-scale image recognition
• global average pooling
• deconvolutional network
• visualizing and understanding convolutional networks
• overlapping pooling
• local response normalization
• imagenet classification with deep convolutionalneural networks
• gradient-based learning applied to document recognition
• functonal requirements
• conceptual design
• requirement analysis
• declarative dml
• procedural dml
• database languages
• view of data
• purpose of database systems
• database-system applications
• database system concepts 7.th
• uniformly most powerful tests
• np lemma
• neyman-pearson lemma
• best critical region
• most powerful tests
• the exponential family
• lehmann-scheffe theorem
• completeness and uniqueness
• rao-blackwell theorem
• any one-to-one function of ss is also ss
• properties of a sufficient statistic
• neyman's factorization theorem
• sufficient statistic
• a sufficient statistic for a parameter
• risk function
• decision function
• mvue
• measures of quality of estimators
• wilks' theorem
• score test
• wald test
• likelihood ratio test
• maximum likelihood test
• asymptotic normality
• bartlett identity
• rao-cramer lower bound
• newton-raphson method
• rao–cramer lower bound and efficiency
• slutzky theorem
• convergence in distribution
• wlln
• weak law of large numbers
• convergence in probability
• bootstrap procedures
• box-muller transformations
• accept-reject method
• monte carlo intergration
• random number generation
• the method of monte carlo
• independence test
• homogeneity test
• goodness-of-fit(gof) test
• chi-square tests
• large sample two-sided test
• additional comments about statistical tests
• introduction to hypothesis testing
• sample percentile
• sample midrange
• sample median
• sample range
• order statistics
• bisection algorithm
• confidence intervals for parameters of discrete distributions
• simple random sample
• interval estimation
• point estimation
• sampling and statistics
• student's theorem
• f distribution
• the multivariate normal distribution
• mixture of normal
• guassian distribution
• beta distribution
• gamma distributions
• the poisson distribution
• negative binomial
• the binomial and related distributions
• 표본 분산에 n-1을 나눠주는 이유
• covaraince
• linear combinations of random variables
• one-to-one transformation case
• many-to-one transformation case
• transformation for several random variables
• variance-covariance matrix
• extension to several random variables
• correlation coefficient
• independent random variables
• law of iterated expectations
• conditional variance
• conditional distributions and expectations
• transformation of discrete r.v.
• deteminant of jacobian
• transformation of continuous r.v.
• transformations : bivariate random variables
• marginal distribution
• distribution of two random variables
• jensen's inequality
• important inequalities
• some special expectations
• linearity of expectation
• expectation of a random variable
• quantiles
• continuous random variables
• discrete random variables
• random variables
• stochastically independent
• mutually independence
• law of total probability
• multiplication rule
• end-to-end memory networks
• inclusion exclusion principle
• sigma field
• the probability set function
• set functions
• demorgan's laws
• distributive laws
• complement set
• mathematical statistics
• advmil
• advmil: adversarial multiple instance learning for the survival analysis on whole-slide images
• fitted value iteration
• value function approximation
• lecture 18
• markov decision process
• mdps & value/policy iteration
• lecture 17
• deepsurv
• aecox
• cox-nnet
• cox regression
• deep learning-based cancer survival prognosis from rna-seq data: approaches and evaluations
• low-level approach
• high-level approach
• comparative analysis of high‑and low‑level deep learning approaches in microsatellite instability prediction
• cpath
• deep learning in histopathology: the path to the clinic
• independent component analysis
• factor anaylsis
• em algorithm & factor analysis
• lecture 15
• expectation-maximization algorithms
• lecture 14
• ablative analysis
• error analysis
• debugging ml models and error analysis
• lecture 13
• backprop & improving neural networks
• lecture 12
• introduction to neural networks
• lecture 11
• decision trees
• empirical risk minimization
• approx/estimation error & erm
• lecture 9
• memory networks
• beam search decoding
• sequence to sequence learning with neural networks
• 눈문 리뷰
• empirical evaluation of gated recurrent neural networks on sequence modeling
• peephole
• lstm: a search space odyssey
• input gate
• output gate
• machine learning students overfit to overfitting
• hold-out validation
• models & cross-validation
• data splits
• lecture 8
• the dual optimization problem
• lecture 7
• batch normalization
• geometric margin
• functional margin
• laplace smoothing
• support vector machines
• lecture 6
• multi-class auc
• an introduction to roc analysis
• gaussian discriminant analysis
• exponential family
• perceptron & generalized linear model
• probabilistic interpretation
• locally weighted
• lecture 3
• adapgrad
• adam : a method for stochastic optimization
• adamax
• an overview of gradient descent optimization algorithms
• matrix derivatives
• lecture2
• dropout: a simple way to prevent neural networks from overfitting
• internal covariate shift
• batch normalization : accelerating deep network training by reducing internal covariate shift
• httperror
• 상수변수
• 함수 몸체
• 포인터를 매개변수로
• 동적 할당 메모리
• implicit cast
• explicit cast
• 숫자승격
• 암시적 형 변환
• 전역 범위
• 지역 범위
• 분산 학습
• kruskal algorithms
• representation of graphs
• accounting method
• potential method
• aggegate analysis
• catalan numbers
• matrix chain multiplication
• left-leaning red-black tree
• llrb
• llrb tree
• 적흑나무
• restructure
• recoloring
• hash tables
• universal hashing
• direct-address table
• direct-address tables
• 단방향 연결리스트
• minimum and maximum
• 최솟값
• data structrue
• 빈 정렬
• 퀵정렬 단점
• 랜덤한 퀵정렬
• a randomized quicksort
• performance of quicksort
• description of quicksort
• 최소 힙 트리
• 최대 힙 트리
• building a heap
• leaf-node
• maintaining the heap property
• max-heapify
• 마스터 정리 증명
• 재귀트리
• recursion tree
• strassen algorithm
• alternate key
• 알고리즘 점화식
• recurrences
• multiplying square matrices
• bigomeganotation
• bigthetanotation
• analyzing algorithms
• algorithms as a technology
• lambda expressions
• 평균 제곱 오차
• 밉시딥1
• 렐루
• 변수의 유효 범위
• rank theorem
• coordinate system
• columns space
• subspaces
• matrix factorizations
• partitioned matrices
• 역행렬의 특징
• characterizations of invertible matrices
• invertible linear transformations
• 역선형변환
• the invertible matrix theorem
• 역행렬정리
• 2x2역행렬공식
• matrix operations
• rotation transformation
• the matrix of a linear transformation
• introduction to linear transformations
• linear transformations
• matrix transformations
• linear dependence
• solution sets of linear systems
• parametric vector form
• nonhomogenenous
• 행렬과 벡터의 곱
• product of matrix and vector
• 행렬방정식
• general solution
• gauss -jordan elimination
• echelon forms
• uniqueness of the rref
• rref
• row operation
• row equivalent
• 공변동
• 결측깞
• desc()
• arrange()
• nycflights13
• 그래프 레이어 문법
• 오버플롯팅
• 통계적변환
• geom_bar
• 데이터분석\
• 심미성매핑
• 25206번
• chebyshev's inequality
• Markov's Inequality
• geom
• Newton's Method
• 버킷 정렬
• one-hot vector
• Candidate Key
• Hypergeometric Distribution
• t distribution
• normal equation
• Bernoulli Distribution
• gauss-jordan elimination
• 선형독립
• skip gram
• AUROC
• find_all()
• Inception v3
• Inception v2
• Network In Network
• mutate
• database schema
• xavier initialization
• 행렬 연산
• ZFNet
• 형식 변환
• summarize
• master method
• AttributeError
• 실버5
• mini batch
• regression tree
• 선형함수
• group normalization
• AVL Tree
• Divide & Conquer
• Adadelta
• 11049
• Inference
• probability mass function
• disjoint
• deconvnet
• 서로소집합
• stochastic depth
• Greedy Algorithms
• polynet
• Densely Connected Convolutional Networks
• inception-v4
• squeeze layer
• fire module
• squeezenet
• wide residual networks
• WRN
• Rethinking the Inception Architecture for Computer Vision
• poisson distribution
• Deep Residual Learning for Image Recognition
• shortcut connection
• Data abstraction
• Greedy decoding
• minibatch
• Nadam
• disjoint set
• tibble
• readr
• tidyr
• dplyr
• 선형종속
• residual learning
• 1193번
• tidyverse
• Beam Search
• Alexnet
• Longest Common Subsequence
• LeNet-5
• subspace
• GRU
• LU factorization
• LU분해
• partitioned matrix
• 분할 행렬
• invertible
• 행렬 곱
• one-to-one
• matrix multiplication
• linearly dependent
• linearly independent
• matrix equation
• linear combination
• 벡터 방정식
• vector equation
• row reduction
• 행 연산
• Q-Q plot
• enqueue
• Relational Data Model
• max pooling
• 1269번
• 분할 상환 분석
• 행상등
• convex function
• 크로스 엔트로피
• double hashing
• 명시적 형 변환
• 대칭차집합
• Conditional Distribution
• geometric distribution
• 선형결합
• 기수 정렬
• heapq
• GLM
• kernels
• RMSProp
• 결측값
• Amortized Analysis
• ResNeXt
• html parsing
• 배치 정규화
• 합집합찾기
• Conditional expectation
• Multinomial distribution
• Chi-Square Distribution
• K-fold cross validation
• Likelihood function
• Heapsort
• set()
• Minimum Spanning Tree
• 2941
• Rod cutting
• Greedy Algorithm
• 그리디 알고리즘
• 완전 이진 트리
• bucket sort
• counting sort
• Long short-term memory
• Bayes' Theorem
• Linear independence
• Invertible matrix
• Fisher information
• Maximum Likelihood Estimation
• Likelihood
• xception
• depthwise separable convolution
• bagging
• Breadth-First Search
• 시그모이드
• vggnet
• 해쉬테이블
• Reference Variable
• 파이썬 라이브러리
• TMB
• bag-of-words
• 분수찾기
• 1193
• underfitting
• 데큐
• 다중 포인터
• 위상정렬
• 병합 정렬
• 1316번
• 회전변환
• 첨도
• cGAN
• DataBase System
• Super Key
• 과적합
• Activation Function
• 활성화함수
• 밑바닥부터 시작하는 딥러닝
• Perceptron
• 퍼셉트론
• ResNet
• seq2seq
• DenseNet
• Regularization
• sigmoid
• 비지도학습
• Union Find
• cross entropy
• 손실함수
• 코딩테스트
• 지도학습
• box plot
• 너비우선탐색
• sample variance
• completeness
• support vector machine
• AUC
• Linear Regression
• 해시 충돌
• gradient descent
• Naive Bayes
• MNIST
• SGD
• elseif
• 인공신경망
• covariance
• Whitening
• K-Means Clustering
• 데이터과학
• unsupervised learning
• chaining
• logistic regression
• 드롭아웃
• Topological sort
• 우선순위 큐
• Depth-First Search
• 보조기억장치
• open addressing
• hash table
• 레퍼런스 변수
• 최댓값
• 해시맵
• 숫자변환
• max heap
• 가설검정
• BST
• filter()
• find()
• homogeneous
• factor analysis
• Resampling
• Boosting
• bigdata
• BigONotation
• Data link layer
• IID
• Directed Graph
• Undirected Graph
• type casting
• object oriented programming
• LRT
• binary search tree
• 메모리주소
• 메모리 주소
• connecting
• select()
• 위치 조정
• Notation
• 삼각수
• Primary Key
• Confidence interval
• B+Tree
• 공분산
• MSE
• 배치처리
• Combination
• central limit theorem
• 시계열
• spanning tree
• urllib
• Normal distribution
• Column space
• session layer
• application layer
• presentation layer
• network layer
• physical layer
• GDA
• CLT
• subset
• Priority Queue
• mongoDB
• facet
• min heap
• DDL
• 해시 함수
• 신뢰구간
• Transmute
• kurtosis
• skewness
• ONTO
• 왜도
• pca
• 그래프그리기
• Foreign key
• CARAT
• dequeue
• p-value
• else if
• 객체지향 프로그래밍
• MLE
• conditional probability
• 버킷
• variance
• basis
• EM Algorithm
• mss
• intersection
• rl
• NAND
• transpose
• permutation
• JITTER
• 탐색
• B-tree
• independent
• 셀렉트
• 최소신장트리
• BFS
• MSD
• endl
• 아스키 코드
• purpose
• CDF
• 1-2
• dl
• 선형변환
• Fill
• 역행렬
• transformation
• parse
• mdp
• 이진법
• 입출력
• Substitution Method
• LCS
• 집합
• 점화식
• Divide and Conquer
• Loop Invariant
• Ensemble
• Efficiency
• REF
• Else
• 전역변수
• 상관관계
• 제어장치
• ALU
• count
• ICA
• 좌표계
• 동적계획법
• probability
• Parser
• 덱
• 앙상블
• CPP
• NIN
• Re
• 삽입 정렬
• SS
• 버블 정렬
• bootstrap
• rename()
• BeautifulSoup
• 재귀함수
• rank
• ERM
• const
• da
• cout
• cin
• struct
• CEE
• 반복문
• do-while
• Radix Sort
• Insertion Sort
• Bubble Sort
• 객체지향언어
• Na
• tuple
• 레지스터
• database
• 구조체
• 14
• ROC
• Algorithm
• switch
• 조건문
• STD
• UMP
• MSI
• DFS
• 큐
• Flatten
• Keys
• 객체
• BIT
• Mean
• Regular Expressions
• Diamonds
• merge sort
• static
• Linked list
• 트리
• sample
• dml
• xor
• or
• and
• 정적변수
• OSI 7 layer
• Attribute
• Set
• span
• Proof
• new
• query
• 분리
• LSD
• while
• Database Design
• Collection
• Delete
• 자연어처리
• position
• OOP
• gap
• Document
• RAM
• 지역변수
• 총정리
• FOR
• If
• PAPER
• 스탠포드
• color
• 함수
• HTTP
• classification
• function
• 명령어
• 데이터
• Ann
• Stack
• PDF
• CNN
• 데이터베이스
• table
• 메모리
• 레퍼런스
• class
• 특징
• CPU
• 유니코드
• CSS
• domain
• DS