Все публикации

[MXDL-1-07] Artificial Neural

[MXDL-1-07] Artificial Neural Network [7/7] - Linear Regression and Non-linear Regression

[MXDL-1-06] Artificial Neural

[MXDL-1-06] Artificial Neural Network [6/7] - Multiclass Classification, Cross entropy loss, Softmax

[MXDL-1-05] Artificial Neural

[MXDL-1-05] Artificial Neural Network [5/7] - Implement an ANN from scratch

[MXDL-1-04] Artificial Neural

[MXDL-1-04] Artificial Neural Network [4/7] - Linearity and Non-linearity, Vanishing Gradient, etc.

[MXDL-1-03] Artificial Neural

[MXDL-1-03] Artificial Neural Network [3/7] - Gradient Descent method and Numerical Differentiation

[MXDL-1-02] Artificial Neural

[MXDL-1-02] Artificial Neural Network [2/7] - Operations of ANN, Objective function

[MXDL-1-01] Artificial Neural

[MXDL-1-01] Artificial Neural Network [1/7] - Introduction to ANN

[MXML-7-04] K-Means clustering

[MXML-7-04] K-Means clustering [4/4] - Finding the optimal number of clusters: Elbow, Silhouette

[MXML-7-03] K-Means clustering

[MXML-7-03] K-Means clustering [3/4] - Implement K-Means++ algorithm from scratch

[MXML-7-02] K-Means clustering

[MXML-7-02] K-Means clustering [2/4] - Implement K-Means clustering from scratch

[MXML-7-01] K-Means clustering

[MXML-7-01] K-Means clustering [1/4] - Basic algorithm for K-Means, Objective function

[MXML-6-10] Support Vector

[MXML-6-10] Support Vector Machine (SVM) [10/10] - Nonlinear Support Vector Regression

[MXML-6-09] Support Vector

[MXML-6-09] Support Vector Machine (SVM) [9/10] - Linear Support Vector Regression

[MXML-6-08] Support Vector

[MXML-6-08] Support Vector Machine (SVM) [8/10] - Multiclass Classification: One-vs-Rest (OvR)

[MXML-6-07] Support Vector

[MXML-6-07] Support Vector Machine (SVM) [7/10] - Multiclass Classification: One-vs-One (OvO)

[MXML-6-06] Support Vector

[MXML-6-06] Support Vector Machine (SVM) [6/10] - Nonlinear SVM: Implementation

[MXML-6-05] Support Vector

[MXML-6-05] Support Vector Machine (SVM) [5/10] - Nonlinear SVM: Kernel trick

[MXML-6-04] Support Vector

[MXML-6-04] Support Vector Machine (SVM) [4/10] - Linear Soft Margin (2): Implementation

[MXML-6-03] Support Vector

[MXML-6-03] Support Vector Machine (SVM) [3/10] - Linear Soft Margin (1)

[MXML-6-02] Support Vector

[MXML-6-02] Support Vector Machine (SVM) [2/10] - Implementation of SVM by solving QP

[MXML-6-01] Support Vector

[MXML-6-01] Support Vector Machine (SVM) [1/10] - Linear hard margin (1), Objective function and QP

[MXML-5-04] Convex Optimization

[MXML-5-04] Convex Optimization [4/4] - Complementary Slackness, Slater's condition, KKT condition

[MXML-5-03] Convex Optimization

[MXML-5-03] Convex Optimization [3/4] - Lagrangian Dual Method for solving quadratic programming

[MXML-5-02] Convex Optimization

[MXML-5-02] Convex Optimization [2/4] - How to solve the EQP and IQP using Lagrange Method