ML

எந்திர கற்றல்

ML என்பதன் சுருக்கம் எந்திர கற்றல்.

என்ன எந்திர கற்றல்?

செயற்கை நுண்ணறிவின் துணைப்பிரிவு (AI) that focuses on developing algorithms and statistical models that enable computer systems to learn and improve their performance on a specific task without being explicitly programmed. In other words, machine learning allows computers to analyze data, identify patterns, and make data-driven predictions or decisions. Here are some key concepts and components of machine learning:

  1. தகவல்கள்: Machine learning relies heavily on data. Algorithms are trained on large datasets, which can include various types of information, such as text, images, numbers, and more.
  2. பயிற்சி: During the training phase, machine learning models are exposed to labeled data, where the desired outcomes or targets are known. The model learns to make predictions or classifications based on this training data.
  3. படிமுறைகள்: Machine learning algorithms are the mathematical and statistical techniques used to make sense of data and extract patterns. There are various types of ML algorithms, including supervised, unsupervised, and reinforcement learning, each suited to different types of tasks.
  4. அம்சங்கள்: Features are the characteristics or attributes of the data that the algorithm uses to make predictions. Feature selection and engineering play a crucial role in improving model performance.
  5. Prediction and Inference: After training, the ML model can make predictions or inferences on new, unseen data. For example, it can predict customer preferences, classify images, detect anomalies, or recommend products.
  6. மதிப்பீடு: The performance of machine learning models is assessed using evaluation metrics specific to the task. Typical metrics include accuracy, precision, recall, F1 score, and mean squared error.
  7. மறுசெயல்முறை: Machine learning is an iterative process. Models are trained, evaluated, and refined repeatedly to improve their accuracy and effectiveness.

Machine learning has a wide range of applications across various industries, including:

  • இயற்கை மொழி செயலாக்கம் (ஆணுக்கு): ML is used for language translation, sentiment analysis, chatbots, and speech recognition.
  • கணினி பார்வை: ML enables image and video analysis, object detection, facial recognition, and autonomous vehicles.
  • ஹெல்த்கேர்: ML is employed in medical diagnosis, drug discovery, and patient outcome prediction.
  • நிதி: ML is used for fraud detection, credit scoring, and stock market analysis.
  • பரிந்துரை அமைப்புகள்: ML powers recommendation engines in e-commerce, content streaming, and social media.
  • தயாரிப்பு: ML is applied for predictive maintenance, quality control, and optimization of production processes.

Machine learning is a technology that allows computers to learn from data and make informed decisions or predictions, making it a powerful tool for solving complex problems and automating tasks in a wide range of domains.

  • சுருக்கமான: ML
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