وفّر 50٪ من خلال الاشتراك السنوي في مجرة واحصل على تصفح لا محدود لأفضل محتوى عربي على الإنترنت.
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هو نوع من التعلم الآلي يتم فيه تدريب الخوارزمية على مجموعة البيانات الكاملة ثم يتم اختبارها على الفور على بيانات جديدة دون المرور بمرحلة التدريب ويستخدم هذا النهج عندما تكون مجموعة البيانات صغيرة، أو عندما تكون عملية التدريب سريعة.
يساعد التعلم الشغوف في تحسين أداء أنظمة الذكاء الاصطناعي من خلال جعلها أكثر كفاءة ودقة. كما يساعد في تقليل كمية البيانات المطلوبة لتدريب أنظمة الذكاء الاصطناعي.
يشير التعلم الكسول إلى عمليات التعلم الآلي التي تتأخر فيها عملية تعميم بيانات التدريب حتى يتم إجراء استعلام على النظام، ويختلف عن التعلم الشغوف في عدة جوانب، إليك أهمها:
التعلم الشغوف قادر على استخدام البيانات من مصادر متعددة، أو البيانات غير المسماة، من أجل إجراء تنبؤات أفضل، ويستخدم التعلم الشغوف في التطبيقات التي يكون فيها الوقت جوهرياً، مثل التشخيص الطبي أو تداول الأسهم. ومن الأمثلة الشهيرة عليها خوارزميات الانحدار الخطي، والشبكات العصبونية الاصطناعية وشجرة القرار.
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