10 Must-Know AI Algorithms for Data Science

Manikandan

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1. Transformer Models

Transformer models like GPT-4 and BERT power key NLP tasks, excelling in context understanding and text generation.

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2. Convolutional Neural Networks (CNNs)

CNNs lead in computer vision, with Vision Transformers gaining traction in specific tasks.

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3. Recurrent Neural Networks (RNNs)

RNNs, including LSTM and GRU, are vital for time-series forecasting and speech recognition.

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4. K-Nearest Neighbors (KNN)

KNN is a simple, effective algorithm used for classification and regression, favored for quick, accurate predictions in 2024.

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5. Random Forest

Random Forest is an ensemble algorithm excelling in classification, regression, and predictive tasks.

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6. Support Vector Machines (SVM)

SVMs are popular for classification tasks in 2024, excelling in image recognition, bioinformatics, and text categorization.

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7. K-Means Clustering

K-Means Clustering is key for unsupervised learning, used in customer segmentation and market analysis in 2024.

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8. Gradient Boosting Machines (GBM)

GBMs like XGBoost and LightGBM excel in predictive tasks, widely used in finance and healthcare for accuracy and precision in 2024.

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9. Reinforcement Learning Algorithms

Reinforcement Learning (RL) algorithms, such as DQN and PPO, excel in robotics, healthcare, and dynamic applications.

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10. Neural Architecture Search (NAS)

Neural Architecture Search (NAS) automates neural network design, optimizing models for various tasks in 2024.

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