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ML Concepts: Math to Algorithms Series' Articles

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What are Vectors and Matrices?

What are Vectors and Matrices?

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3 min read
What are Matrix Operations?

What are Matrix Operations?

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3 min read
Understanding the Basics: Linear Equations and Matrices

Understanding the Basics: Linear Equations and Matrices

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4 min read
Eigenvalues and Eigenvectors: Unveiling the Secrets of Data Transformation in Machine Learning

Eigenvalues and Eigenvectors: Unveiling the Secrets of Data Transformation in Machine Learning

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3 min read
Understanding Derivatives: The Slope of Change

Understanding Derivatives: The Slope of Change

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4 min read
Unveiling the Secrets of Multivariable Calculus: Partial Derivatives, Chain Rule, and Machine Learning

Unveiling the Secrets of Multivariable Calculus: Partial Derivatives, Chain Rule, and Machine Learning

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3 min read
Gradient Descent Optimization: The Core Algorithm Explained

Gradient Descent Optimization: The Core Algorithm Explained

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4 min read
What is Conditional Probability?

What is Conditional Probability?

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3 min read
What is Bayes' Theorem?

What is Bayes' Theorem?

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4 min read
What are Probability Distributions?

What are Probability Distributions?

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4 min read
Unveiling the Secrets of Your Data: A Deep Dive into Descriptive Statistics

Unveiling the Secrets of Your Data: A Deep Dive into Descriptive Statistics

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3 min read
Unveiling the Secrets of Data: Confidence Intervals and Hypothesis Testing in Machine Learning

Unveiling the Secrets of Data: Confidence Intervals and Hypothesis Testing in Machine Learning

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3 min read
What is Machine Learning?

What is Machine Learning?

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4 min read
What is Simple Linear Regression?

What is Simple Linear Regression?

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3 min read
Diving Deep: The Mechanics of Multiple Linear Regression

Diving Deep: The Mechanics of Multiple Linear Regression

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4 min read
Taming the Wild Beast: Understanding Ridge and Lasso Regression

Taming the Wild Beast: Understanding Ridge and Lasso Regression

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3 min read
Diving Deep into Logistic Regression: Sigmoid, Probabilities, and Predictive Power

Diving Deep into Logistic Regression: Sigmoid, Probabilities, and Predictive Power

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4 min read
Decoding the Magic: Logistic Regression, Cross-Entropy, and Optimization

Decoding the Magic: Logistic Regression, Cross-Entropy, and Optimization

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4 min read
Understanding the KNN Algorithm: Finding Your Nearest Neighbors

Understanding the KNN Algorithm: Finding Your Nearest Neighbors

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3 min read
Unlocking the Power of Support Vector Machines: Hyperplanes and Margin Maximization

Unlocking the Power of Support Vector Machines: Hyperplanes and Margin Maximization

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3 min read
The Core Idea: Finding the Best Separator

The Core Idea: Finding the Best Separator

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3 min read
Understanding Decision Trees

Understanding Decision Trees

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3 min read
Understanding Information Gain: Choosing the Right Questions

Understanding Information Gain: Choosing the Right Questions

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3 min read
What are Ensemble Methods, Bagging, and Random Forests?

What are Ensemble Methods, Bagging, and Random Forests?

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3 min read
What are Ensemble Methods and Boosting?

What are Ensemble Methods and Boosting?

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4 min read
What is K-Means Clustering?

What is K-Means Clustering?

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3 min read
Unveiling the Secrets of Data Grouping: A Deep Dive into Hierarchical Clustering and DBSCAN

Unveiling the Secrets of Data Grouping: A Deep Dive into Hierarchical Clustering and DBSCAN

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3 min read
Understanding the Core Concepts: From Data Mountains to Informative Peaks

Understanding the Core Concepts: From Data Mountains to Informative Peaks

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3 min read
What is PCA? A Simplified Explanation

What is PCA? A Simplified Explanation

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3 min read
Decoding the Metrics: Understanding Model Evaluation in Regression

Decoding the Metrics: Understanding Model Evaluation in Regression

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3 min read
Decoding the Detective Work: Understanding Model Evaluation Metrics for Classification

Decoding the Detective Work: Understanding Model Evaluation Metrics for Classification

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4 min read
Decoding the Secrets of Your Machine Learning Model: Confusion Matrices, ROC Curves, and AUC

Decoding the Secrets of Your Machine Learning Model: Confusion Matrices, ROC Curves, and AUC

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3 min read
Diving Deep: K-Fold Cross-Validation

Diving Deep: K-Fold Cross-Validation

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3 min read
What is the Bias-Variance Trade-off?

What is the Bias-Variance Trade-off?

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3 min read
Diving Deep: Understanding the Mechanics

Diving Deep: Understanding the Mechanics

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3 min read
The Perceptron: The Brain Cell of a Neural Network

The Perceptron: The Brain Cell of a Neural Network

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Decoding the Neural Network's Mind: A Journey Through Forward Propagation

Decoding the Neural Network's Mind: A Journey Through Forward Propagation

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3 min read
What is Backpropagation?

What is Backpropagation?

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3 min read
Understanding Convolutions: The Sliding Window of Insight

Understanding Convolutions: The Sliding Window of Insight

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3 min read
Understanding the Sequential Nature of Data

Understanding the Sequential Nature of Data

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3 min read
The Vanishing Gradient Problem: A Memory Lapse in RNNs

The Vanishing Gradient Problem: A Memory Lapse in RNNs

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4 min read
What is Transfer Learning?

What is Transfer Learning?

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3 min read
Core Concepts: Decoding Human Language

Core Concepts: Decoding Human Language

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3 min read
What is Computer Vision?

What is Computer Vision?

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3 min read
The Moral Machine: Ethics in AI and the Rise of MLOps

The Moral Machine: Ethics in AI and the Rise of MLOps

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3 min read