@cherubim

kirubel Awoke

@cherubimJoined May 2025

insights in machine learning, mathematics, and beyond.

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kirubel Awoke's blogs

Data Balancing in Machine Learningcherubim.hashnode.dev1 post

Data balancing in Machine learningseraphim.hashnode.dev1 post

Linear Transformations and Deep Learningunsearchable.hashnode.dev1 post

Support Vector machine and Maths behindunsearchable1.hashnode.dev1 post

Random Forest and Maths behind itunsearchable2.hashnode.dev1 post

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Recently published

KAkirubel Awokeunsearchable2.hashnode.devMay 14, 2025 · 6 min read

Random Forest and Math behind it

Random Forest is one of machine learning algorithms that is an ensemble method combining \(T\) decision trees \(\{ h_t \}_{t=1}^{T}\) , where each tree is trained on: A bootstrap sample from the dataset (bagging), A random subset of features at eac...

KAkirubel Awokeunsearchable1.hashnode.devMay 13, 2025 · 6 min read

Support Vector Machine and Math behind it

Support vector machine is a machine learning algorithm used for classification and regression. SVM uses hyperplane to separate data into groups maximizing the distances between the closest points (vectors) for each class (group). In machine learning,...

KAkirubel Awokeunsearchable.hashnode.devMay 7, 2025 · 9 min read

Linear Transformation and Deep Learning

Introduction to Linear Transformations A linear transformation is a mathematical concept used to map vectors from one space to another while preserving the operations of vector addition and scalar multiplication. It is defined as a function \(T\) tha...

KAkirubel Awokeseraphim.hashnode.devMay 6, 2025 · 3 min read

Data Balancing in ML using SMOTE

(SMOTE)As we have seen earlier, one of the methods for data balancing in ML is using naive random over-sampling by generating new samples in the underrepresented classes by randomly duplicating samples from the minority classes until all classes are ...

KAkirubel Awokecherubim.hashnode.devMay 5, 2025 · 4 min read

Data Balancing in Machine Learning

Imbalanced classification refers to a scenario where the target classes do not have equal representation. For example, in medical diagnosis: Class 0 (Rare Disease): 50 samples Class 1 (Common Case): 5000 samples Why Does Data Imbalance Matter? B...

kirubel Awoke

About

Available for

kirubel Awoke's blogs

Recently published

Random Forest and Math behind it

Support Vector Machine and Math behind it

Linear Transformation and Deep Learning

Data Balancing in ML using SMOTE

Data Balancing in Machine Learning

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kirubel Awoke

About

Available for

kirubel Awoke's blogs

Recently published

Random Forest and Math behind it

Support Vector Machine and Math behind it

Linear Transformation and Deep Learning

Data Balancing in ML using SMOTE

Data Balancing in Machine Learning