GET UP TO DATE WITH A NEW PERSPECTIVE ON MACHINE LEARNING, DATA SCIENCE, AND 3D PRINTING
Algebra plus Geometry equal Calculus: A Detailed Explanation to Understand Three-Feature Equations on 4D Movements Applications for AI
Cosine Equation with Three Features for 4D Surfaces: Applications on Algebra, Geometry, Calculus, and AI - Google Colab
markov_projection_final_v0_1.ipynb - New Methodology for Stock Prices Estimates Without Sklearn - Google Colab
TOP95¹ ETFs in USA, 30/10/2023: Code Developed by ML Perspective Achieves 50% -VanEck Semiconductors SMH- and 25% -XLK ETF- in Returns
The Hyperspace is not Always Euclidean: f1 Scores in Positive/Negative Curvature Using Eigenvectors and Sklearn - Part VI
The Hyperspace is not Always Euclidean: UPDATED - Study of f1 Score with Sklearn Metrics - Part V (Colab)
All¹ ETFs in Europe, 30/10/2023: Profitability Shifts to Greece with National Bank of Greece (ETE) and Mytilineos (MYTIL) as Main Actors
prior_to_MGMv4_1_BETA_30_11_2023.ipynb - New Features for Data Analysis of Stock Prices with Sklearn
formulas_1_0_2023_vrs_BETA.ipynb - Google Colab - formula and class definition in Python
TOP10 ETFs in USA: Above Zero Probabilities and Maximum Likelihood Returns Towards 03/07/2023
TOP95¹ ETFs in USA, 03/07/2023: AI Drives Development Across Industries, Taiwan Semiconductors Leads
Data is Nor 2D Neither 3D but 4D... or Higher
The Hyperspace is not Always Euclidean: f1 Score in Positive Curvature Fits Best Data - Part IV
LATAM ETFs in USA, 03/07/2023: Bolsa Mexicana de Valores BMV Upwards as AMX, LABB, FEMSA Gain
Markov General Model (MGM) Decimals v4.0 BETA to Calculate Adv. Statistics for Multiple Securities
All¹ ETFs in Europe, 03/07/2023: SMI and CAC Keep Attractiveness Despite Rate Hike and Civil Unrest
All ETFs¹ in Europe: Above Zero Probabilities and Maximum Likelihood Returns Towards 03/07/2023
TOP95 ETFs in USA: Above Zero Probabilities and Maximum Likelihood Returns Towards 16/01/2023
Top10 ETFs in USA, 10/04/2023: QQQ Top Profitable ETF, Techs Keep the Momentum
The Hyperspace is not Always Euclidean: Study of f1 Scores with Sklearn Metrics - Part II