Definition of Machine Learning

Importance of Machine Learning

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Vectors and Matrices

Matrix Operations

Eigenvectors and Eigenvalues

Derivatives

Gradient Descent

Optimization Algorithms

Probability Theory

Statistical Distributions

Hypothesis Testing

Data Sources

Missing Data Handling

Outlier Detection and Treatment

Feature Selection

Feature Extraction

Feature Scaling

Simple Linear Regression

Multiple Linear Regression

Regularization Techniques

Binary Logistic Regression

Multinomial Logistic Regression

Evaluation Metrics

Linear SVM

Non-linear SVM

Kernel Functions

K-means Clustering

Hierarchical Clustering

Density-Based Clustering

Principal Component Analysis (PCA)

Singular Value Decomposition (SVD)

t-Distributed Stochastic Neighbor Embedding (t-SNE)

Apriori Algorithm

FP-Growth Algorithm

Architecture of Neural Networks

Activation Functions

Backpropagation Algorithm

Convolutional Layers

Pooling Layers

Convolutional Operations

Long Short-Term Memory (LSTM)

Gated Recurrent Unit (GRU)

Sequence Generation

k-fold Cross-Validation

Stratified Cross-Validation

Leave-One-Out Cross-Validation

Accuracy

Precision, Recall, and F1 Score

Receiver Operating Characteristic (ROC) Curve

Grid Search

Random Search

Model Selection

Exporting Models

Cloud Deployment

Containerization

Natural Language Processing (NLP)

Computer Vision

Recommender Systems