Core Machine Learning | Incognition

Core Machine Learning

Core Machine Learning

Learn the complete supervised + unsupervised machine learning workflow from raw data to trained models.

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Why Data Preprocessing Matters

Exploratory Data Analysis (EDA)

Cleaning Dirty Data

Handling Missing Values

Removing Duplicate Data

Detecting Outliers

Encoding Categorical Variables

Feature Scaling

Standardization

Feature Engineering

Train, Validation & Test Split

How Does a Machine Actually Learn?

The Cost Function

Gradient Descent

The Learning Rate

Batch Gradient Descent

Stochastic Gradient Descent

Mini-Batch Gradient Descent

Convex vs Non-Convex Optimization (Intuition)

Bias vs Variance

Overfitting vs Underfitting

What is Supervised Learning?

Regression vs Classification

Linear Regression

Multiple Linear Regression

Polynomial Regression

Logistic Regression

Sigmoid Function

K-Nearest Neighbors

Support Vector Machines

Decision Boundaries

Binary vs Multi-Class Classification

Choosing the Right Supervised Learning Algorithm

What is Unsupervised Learning?

Similarity & Distance Metrics

K-Means Clustering

Choosing K (How Many Clusters?)

Hierarchical Clustering

Principal Component Analysis (PCA)

Comparing Unsupervised Learning Algorithms