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DataCamp for Business 체험강의 설명
선수 조건
Supervised Learning with scikit-learn1
Preparing data and a linear model
In this chapter, we will learn how machine learning can be used in finance. We will also explore some stock data, and prepare it for machine learning algorithms. Finally, we will fit our first machine learning model -- a linear model, in order to predict future price changes of stocks.
2
Machine learning tree methods
Learn how to use tree-based machine learning models to predict future values of a stock's price, as well as how to use forest-based machine learning methods for regression and feature selection.
3
Neural networks and KNN
We will learn how to normalize and scale data for use in KNN and neural network methods. Then we will learn how to use KNN and neural network regression to predict the future values of a stock's price (or any other regression problem).
4
Machine learning with modern portfolio theory
In this chapter, you'll learn how to use modern portfolio theory (MPT) and the Sharpe ratio to plot and find optimal stock portfolios. You'll also use machine learning to predict the best portfolios. Finally, you'll evaluate performance of the ML-predicted portfolios.
Python으로 배우는 금융 분야 Machine Learning
강의 완료
DataCamp for Mobile을 통해 데이터 분석 능력을 향상시키세요.
모바일 강좌와 매일 5분 코딩 챌린지를 통해 이동 중에도 학습 효과를 높이세요.