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ML-BASIC. PART 5-1. Gradient-based Optimization
02-14
ML-BASIC. PART 6. Backpropagation
02-11
ML-BASIC. PART 5. Optimization Methods
02-10
ML-BASIC. PART 4. Distributions & Loss Function
02-07
ML-BASIC. PART 3. Probability
02-06
ML-BASIC. PART 2. Hypothesis Set
02-05
ML-BASIC. Part 1. Overview
02-04
ML4NLP. PART 1. Text Classification & Sentence Representation 2
02-19
ML4NLP. PART 1. Text Classification & Sentence Representation 1
02-18
Python. 정규 표현식(Regular Expression) - 1
04-28
Python. 매직 메소드(Magic Method)
04-21
Python. 정적 메소드(@classmethod & @staticmethod)
04-20
Python. @Property
04-20
Python. List Comprehension
04-15
Python. functools.reduce()
04-14
Python. Asterisk(*) Operator
04-14
Python. Lambda Expression
04-12
Python. Generator
04-03
Python. Iterator
03-29
Python. itertools.chain()
03-26
Python. itertools.accumulate()
03-26
Python. itertools.product()
03-24
Python. itertools.combinations()
03-23
Python. itertools.permutations()
03-19
Python. itertools.takewhile()
03-15
Python. itertools.dropwhile()
03-14
Python. itertools.cycle()
03-13
Python. collections.Counter()
03-13
Tensorflow Basic. Overview of the tensorflow
04-16
Algorithm. 행렬의 대각 성분을 출력하는 방법
06-22
Survival Analysis. Cox 비례 위험 모형(Cox Proportional Hazard Model) - 1
08-12
Survival Analysis. 로그 순위법 (Log-Rank Test)
07-31
Survival Analysis. 카플란-마이어 추정 (Kaplan Meier Estimation)
07-29