Federated Learning Systems: Towards Privacy-Preserving Distributed AI
Muhammad Habib ur Rehman · Mohamed Medhat Gaber
apr, 2025 · Springer Nature
E-kitob
165
Sahifalar soni
reportReytinglar va sharhlar tasdiqlanmagan Batafsil
Bu e-kitob haqida
This book dives deep into both industry implementations and cutting-edge research driving the Federated Learning (FL) landscape forward. FL enables decentralized model training, preserves data privacy, and enhances security without relying on centralized datasets. Industry pioneers like NVIDIA have spearheaded the development of general-purpose FL platforms, revolutionizing how companies harness distributed data. Alternately, for medical AI, FL platforms, such as FedBioMed, enable collaborative model development across healthcare institutions to unlock massive value.
Research advances in PETs highlight ongoing efforts to ensure that FL is robust, secure, and scalable. Looking ahead, federated learning could transform public health by enabling global collaboration on disease prevention while safeguarding individual privacy. From recommendation systems to cybersecurity applications, FL is poised to reshape multiple domains, driving a future where collaboration and privacy coexist seamlessly.
Bu e-kitobni baholang
Fikringizni bildiring.
Qayerda o‘qiladi
Smartfonlar va planshetlar
Android va iPad/iPhone uchun mo‘ljallangan Google Play Kitoblar ilovasini o‘rnating. U hisobingiz bilan avtomatik tazrda sinxronlanadi va hatto oflayn rejimda ham kitob o‘qish imkonini beradi.
Noutbuklar va kompyuterlar
Google Play orqali sotib olingan audiokitoblarni brauzer yordamida tinglash mumkin.
Kitob o‘qish uchun mo‘ljallangan qurilmalar
Kitoblarni Kobo e-riderlar kabi e-siyoh qurilmalarida oʻqish uchun faylni yuklab olish va qurilmaga koʻchirish kerak. Fayllarni e-riderlarga koʻchirish haqida batafsil axborotni Yordam markazidan olishingiz mumkin.
