Laboratory of Intelligent Networks at KoreaTech
“Student-teacher relationships are based on trust. Acts, which violate this trust, undermine the educational process. Your classmates and the instructor will not tolerate violations of academic integrity”
Sept. 06 – 과목 소개 및 anaconda(Python)+jupyter(ipython)+Spark 코딩 환경 구축
본 수업에서 활용할 프로그래밍 환경
2) spark-2.0.0 설치
spark 환경 설정
export SPARK_HOME=”/Users/[Your Home]/spark-2.0.0-bin-hadoop2.7″
export PYTHONPATH=”$SPARK_HOME/python/lib/py4j-0.10.1-src.zip”
export PATH=”$SPARK_HOME/bin:$PATH”
3) findspark 모듈 설치
4) tensorflow 라이브러리 설치
Terminal에서 Anaconda Navigator 실행
대부분의 경우 없을 것이며 Terminal 에서 다음과 같이 설치
5) jupyter notebook 실행
6) 다음 테스트 프로그램 수행이 되면 환경 구성 완료
7) 숙제 제출 방법
파이썬 학습
첫번째 숙제
Sept. 13 – Data Science 101
Apache Spark Tutorial (Edx BerkeleyX CS105x)
Python+Spark 학습
Introduction to Apache Spark (Source: Edx BerkeleyX CS105x)
Sept. 20 – Supervised vs. Unsupervised Learning, Predictive Model, Data Handling and EDA (Exploratory data analysis)
Sept. 27 – Decision Tree and Random Forest
Oct. 04 – Practice – Decision Tree and Random Forest
Oct. 11 – Linear Regression and Gradient Descendent
Oct. 18- Logistic Regression
Nov. 01 – Neural Network I
Nov. 08 – Neural Network (Back Propagation) II
Nov. 15 – K-Nearest Neighbors
Nov. 22 – K-Means
Nov. 29 – Convolutional Neural Network