Back propagation ek mahatvapurnn technique hai machine learning mein, jo humein yeh sikhata hai ki kaise hum apne model ko behtar bana sakte hain.
Machine learning ek aise shakha hai jo computers ko sikhaata hai ki kaise kuchh aisa karne mein mahir ho jaye, jo hum insan bina kisi manual intervention ke nahi kar sakte.
Back propagation ek mahatvapurnn technique hai machine learning mein, jo humein yeh sikhata hai ki kaise hum apne model ko behtar bana sakte hain.
back propagation in machine learnin article mein, hum back propagation ko saral shabdo mein samjhne ki koshish karenge.
aur ek khas baat, Machine Learning kya hain detail me janne ke liye "what is machine learning in hindi" par click kare.
 |
| back-propagation-in-machine-learning-in-hindi |
Machine Learning (Machine Shikshan)
Machine learning ek aisa computer science ka kshetra hai jahan par computers ko sikhaya jata hai ki kaise woh data se seekh sakte hain aur naye jankari prapt kar sakte hain.
Ismein, hum algorithms ka istemal karte hain jo data se patterns ya trends dhundhte hain aur phir naye data ko predict karne mein istemal hote hain.
Neural Networks (Tantrik Jaal)
Ek prakar ke machine learning model hote hain jise neural network kehte hain.
Yeh model hamare dimag ke tarah kaam karte hain aur data ko process karke samjhne ka prayaas karte hain.
Neural network ek set hoti hai layers ke, aur har layer mein kai neurons hote hain jo data ko process karte hain.
Feedforward (Data Prachar)
Neural network ke pratham step mein, data ek tarah se input layer mein pravesh karti hai aur phir isi data ko har ek layer ke through process kiya jata hai, aur output layer tak pahunchti hai.
Yeh step feedforward ke roop mein jana jata hai.
Back Propagation (Piche ki Or Prachar)
Back propagation ek technique hai jisse hum apne neural network ko sikhate hain ki kaise woh apne mistakes se seekh sakte hain.
Ismein, hum errors ko detect karte hain aur fir un errors ko har ek layer ke wapas bhejte hain, tak ki woh apne parameters ko sudhar sakein.
Error Calculation (Error Ganana)
Sabse pehle, humein errors ko calculate karna hota hai.
Yeh error woh difference hoti hai jo humare neural network ke output aur actual output mein hoti hai.
Is error ko minimize karna hamara lakshya hota hai.
Gradient Descent (Gradient Girna)
Error ko minimize karne ke liye, hum gradient descent ka istemal karte hain.
Ismein, hum errors ko kam karne ke liye har ek layer ke parameters ko thoda-thoda change karte hain.
Yeh process iteration ke roop mein hoti hai aur neural network apne mistakes se seekhta rahta hai.
Learning Rate (Sikhne Ki Dar)
Learning rate ek mahatvapurnn parameter hoti hai jo decide karta hai ki kitni tezi se neural network sikh raha hai.
Agar learning rate jyada ho, to network unstable ho sakta hai, aur agar kam ho, to sikhne mein deri ho sakti hai.
Conclusion
Back propagation ek mahatvapurnn machine learning technique hai jo humare neural network ko sikhata hai ki kaise woh apne mistakes se sikh sakein aur behtar ho sakein.
back propagation in machine learning article mein humne is technique ko saral shabdo mein samjhaya hai, taki koi bhi aasani se samajh sake.
Machine learning aur back propagation ke saath khelna ek naye digital yug mein hamare liye ek naye safar ka arambh hai.
Call to Action
Agar aapko machine learning aur back propagation ke bare mein aur adhik jankari chahiye, to kripya karke hamare aur articles padhein aur apne gyaan ko badhayein.
Machine learning ek aisa shikshan kaushal hai jo aane wale samay mein aur bhi mahatvapurnn hoga.
COMMENTS