Federated Learning - Wat is dit?,en?
Oorsig
Machine learning aangesien 'n begrip niks nuuts is nie,,en,Google het gewerk aan 'n nuwe konsep genaamd Federated Learning wat kan herdefinieer hoe rekenaars uit data leer,,en,Anders as in die geval van,,en,gebruikersdata word op smartphone-apps gestoor,,en,Die programme leer mettertyd uit gebruikersdata en insette en word intuïtiewer,,en,Gebruikerdata is nie gesentraliseer nie,,en,Daar word geglo dat Federated Learning vinniger dataverwerking en meer privaatheid van data tot gevolg sal hê,,en,Daar moet kennis geneem word dat die konsep nuut is en dat Google aan potensiële probleme werk, soos oormatige belasting,,en,verwerkers,,en,dit lyk nie of Google die konsep van 'n baanbreker was of besit nie,,en,Apple het reeds aan hierdie konsep gewerk,,en,weliswaar met 'n ander naam,,en,Wat is Federated Learning,,en,Federated Learning is 'n leerproses vir masjiene,,en. You come across various examples of machine learning in your day to day lives. Recommendations provided by an ecommerce website is, byvoorbeeld, an outcome of machine learning. Google has been working on a new concept known as Federated Learning which can redefine how computers learn from data. Unlike in the case of machine learning, user data is stored on smartphone apps. The apps learn from user data and inputs over time and become more intuitive. User data is not centralized. It is believed that Federated Learning will result in quicker data processing and more data privacy. This needs to be noted that the concept is new and Google is working on potential problems like excessive load on smartphone processors. Also, it does not seem that Google pioneered or owns the concept. Apple had already worked on this concept, albeit with a different name.
What is Federated Learning?
Federated Learning is a learning process for machines. Dit word nou spesifiek op slimfone toegepas met die,,en,bedryfstelsel,,en,Die programme op die slimfoon leer van gebruikersinsette soos sleutelwoorde en verryk die algoritmes,,en,Gebaseer op die leer,,en,programme kan baie take verrig, soos aangepaste aanbevelings,,en,Om die idee uit te voer,,en,Google gebruik sy eie sleutelbord GBoard op die slimfone om gebruikersinsette te aanvaar,,en,Dit het ook 'n ligter weergawe daarvan geïmplementeer,,en,sagteware Tensorflow op die slimfone,,en,Anders as in masjienleer,,en,gebruikersdata word nie in die wolk gestoor nie, maar op die apps,,en,gebruikersdata is vinniger beveilig en verwerk,,en,Verskil tussen federale leer en masjienleer,,en,Die belangrikste verskille is,,en,Stoor van data,,en,Vir masjienleer,,en,alle gebruikersdata word in die wolk gestoor, maar vir federale leer,,en Android operating system. The apps on the smartphone learn from user inputs such as keywords and enrich the algorithms. Based on the learning, apps can do a lot of tasks such as provide tailored recommendations. To put the idea into practice, Google is using its own keyboard GBoard on the smartphones for accepting user inputs. It has also implemented a lighter version of its machine learning software Tensorflow on the smartphones. Unlike in machine learning, user data is not stored in the cloud but on the apps. So, user data is more secured and processed quicker.
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Difference between Federated Learning and Machine Learning
The main differences are:
- Data storage: For machine learning, all user data is stored in the cloud but for federated learning, die gebruikersdata word in die slimfoontoep gestoor,,en,algoritme,,en,die algoritmes word ontwikkel of bygewerk op grond van opgehoopte gebruikersdata,,en,Vir federale leer,,en,pasgemaakte algoritmes word ontwikkel op grond van gebruikersdata,,en,Programopdatering,,en,Masjienleer is afhanklik van programopdaterings, terwyl federale leer dit nie doen nie,,en,Hoe kan Federated Learning leer herdefinieer?,,en,Federated Learning beloof om programme se vaardighede in die leer van gebruikersinsette vinniger te verbeter,,en,Programme kan verbeterde gebruikerservaring bied, soos beter produkaanbevelings,,en,beperkings,,en,Daar word geglo dat die verwerking van hoë volume data baie druk op die slimfoonbattery en -verwerker sal uitoefen,,en,Federated Learning lyk soos 'n belowende idee,,en,Dit kan verbeter hoe apps by verskillende gebruikersdata aanpas en die voordele daaraan bied,,en.
- Algorithm: For machine learning, the algorithms are developed or updated based on accumulated user data. For federated learning, custom algorithms are developed based on user data.
- App update: Machine learning is dependent on app updates while federated learning is not.
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How can Federated Learning redefine learning?
Federated Learning promises to improve apps’ capabilities in learning from user inputs and quicker. Apps can offer improved user experience such as better product recommendations.
Limitations
It is believed that high volume data processing will exert a lot of pressure on the smartphone battery and processor.
Gevolgtrekking
Federated Learning seems like a promising idea. It can improve how apps adapt to diverse user data and return the benefits. Die sleutelpunte daarvan is beter leervaardighede, gebruikerservaring en meer privaatheid van data,,en,Lees meer interessante artikels oor Masjienleer,,en,Federale leer,,en,masjienleer-algoritmes,,en,techalpine.com/federated-learning-what-is-it,,en.
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