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Machine Learning

Machine learning enables computers to learn from data and make predictions or decisions without being explicitly programmed for every scenario.

Overview

Machine learning involves building algorithms that can learn from data and make predictions or decisions. ML models improve their performance through experience with data.

Machine learning includes supervised learning (classification, regression), unsupervised learning (clustering), and deep learning (neural networks).

Key Technologies

Frameworks

scikit-learn
XGBoost
Keras

Languages

Julia
MATLAB

Tools

MLflow
Weights & Biases
TensorBoard

Key Concepts

Supervised Learning

Train models on labeled data to make predictions or classifications.

Unsupervised Learning

Discover patterns in unlabeled data through clustering and dimensionality reduction.

Deep Learning

Build neural networks with multiple layers to learn complex patterns in data.

Model Evaluation

Evaluate model performance using metrics like accuracy, precision, recall, and F1 score.

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