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Python_CS_03

Algorithmic Trading in Python

Case-Study Title: Using Classification algorithms in financial markets (Stock Market Prediction)

Data Analysis methodology: CRISP-DM

Dataset: S&P-500 (The Standard and Poor's 500) Timeseries data from 2019 to 2023

Case Goal: Create an automatic financial trading algorithm for S&P-500 index (Algorithmic Trading)

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Algorithmic Trading in Python

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python data-science machine-learning random-forest numpy svm scikit-learn sklearn pandas algo-trading naive-bayes-classifier classification data-analysis logistic-regression lda support-vector-machines algorithmic-trading statsmodels linear-discriminant-analysis gaussian-naive-bayes

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