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luminary.blog
by Oz Akan

Technical

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Posts in 2025

  • $XGBoost: The Powerhouse of Gradient Boosting

    XGBoost is one of the most powerful tools for building machine learning models due to its speed, accuracy, and robustness.

    wolf
  • $What are Word Embeddings?

    Word embeddings are a fundamental concept in Natural Language Processing (NLP), enabling machines to understand and process human language effectively.

    numbers
  • $Three Terms To Know About Quantum Computers

    Quantum computing leverages three foundational principles—error suppression, superposition, and entanglement—to achieve computational advantages unattainable by classical systems.

    cpu
  • $SageMaker Built-in Algorithms

    Amazon SageMaker offers a wide range of built-in algorithms to simplify and accelerate machine learning (ML) projects.

    wolf
  • $Factorization Machines

    Factorization Machines (FMs) are a type of machine learning model that helps us make predictions based on data.

    art wolf
  • $What are Quantum Chips?

    Due to superposition and entanglement, a quantum computer can, for certain problems, explore a vast number of possibilities in parallel, potentially solving some problems much faster than classical computers.

    cpu
  • $SageMaker Linear Learner Algorithm

    Amazon SageMaker Linear Learner is a machine learning algorithm that helps solve two main types of problems.

    wolf
  • $What are Features in Machine Learning?

    Choosing the right features is crucial for building an accurate and efficient model.

    bird
  • $The ML Development Lifecycle and Best Practices

    A comphrensive guide to ML Development Lifecycle with best practices.

    rabbit
  • $Ocelot - Amazon Quantum Chip

    By focusing on better error suppression at the physical level, rather than just adding more qubits, Amazon is attempting to make the path to practical quantum computing more efficient and achievable in the near term.

    atom