Track 2: Machine Learning

Machine Learning focuses on computational methods that allow systems to learn from data, identify patterns, generate predictions, and continuously improve their performance. This track covers fundamental and advanced machine learning algorithms, model development, feature engineering, optimization, and evaluation techniques. It also highlights scalable and practical approaches for deploying machine learning models across different applications and environments.

  • Supervised, Unsupervised & Semi-Supervised Learning

  • Reinforcement Learning & Self-Supervised Learning

  • Feature Engineering, Model Selection & Optimization

  • AutoML, Transfer Learning & Model Deployment

    Track 2: Machine Learning Conference Speakers

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