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Machine Learning on Stock Data with Python and SciKit
(Prerequisite) Machine Learning Introduction
00A What Is Machine Learning (5:26)
00B Types Of Machine Learning Models (12:17)
00C What Is Supervised Learning (11:04)
00D What Is Unsupervised Learning (8:17)
01 How Does A Machine Learning Agent Learn (7:38)
02 What Is Inductive Learning (4:11)
03 Performance Of A Machine Learning Algorithm (4:14)
04 Handle Noise In Data (5:22)
05 Powerful Tools With Machine Learning Libraries- (12:11)
Build linear regression ML model with stocks
01 Load And Visualize Google Drive Data In Python (6:54)
02 Process Amazon Stock Data For Machine Learning (6:19)
03 Build Linear Regression Ml Model With Stocks (5:02)
Source files
Intro to KMeans ML
05A What Is Unsupervised Learning (8:17)
05B What Is K Means Clustering (11:58)
KMeans clustering machine learning on S&P stocks
01 Import S&P Stock Data Into Colab (6:09)
02 S&P Data Processing And Cleaning For Machine Learning (4:51)
03 Calculate Average S&P Returns With Python (2:48)
04 Calculate Average S&P Variances With Pandas (3:19)
05 Determine Optimal Number Of Clusters For Kmeans (8:38)
06 Build A Kmeans Unsupervised Model For S&P (5:47)
Source files
01 Import S&P Stock Data Into Colab
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