@watchdizmama: Please help one of our local living heroes starting this national heroes day. #readingclub2000 #mangnanie #BookTok #reading

Watchdizmama | Margaret
Watchdizmama | Margaret
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Region: PH
Monday 31 August 2026 02:42:24 GMT
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_lovekhrizia
Khrizia Poblador :
Upppppppp
2026-09-11 11:02:11
4
ba52838
bôa :
random dot.
2026-09-08 11:16:33
4066
itschippy3
chippy :
why does the government in the Philippines dont invest for a free public library
2026-09-08 19:01:26
9738
ladyjean555
femmebot5𖹭 :
This is the "data center" that needs to be funded. Not that pax silica bullsh1t!!!
2026-09-08 19:24:12
1639
blxss_7
blxss_7 :
matcha or coffee???
2026-09-08 02:23:30
373
vveomgy
linda walker ۶۟ৎ :
booost
2026-09-10 12:16:13
2
sharaia.vlr
SharaiaValer :
See mang danny doesnt need to be politician to help😂
2026-09-09 00:35:26
3361
maesteriie
Mae 🌻 :
This is worth supporting. Supporting Mang Nani and his advocacy! 🔥
2026-09-09 18:12:59
2
catswithheelboots
sinigang na hakdog :
i do hope things fo well for him and that the weather will be better for them
2026-08-31 10:59:26
2632
nicakeith07
Nica :
Heart jar
2026-09-09 01:44:49
120
jemlessgem
aestherielle. :
BOOSTING! WHAT'S YOUR FAVORITE COLOR?
2026-09-09 03:54:22
170
jamrhi08
jamrhi08 :
Random dot.
2026-09-09 13:36:31
56
phoootakayongmgalalake
babygen :
random hearts
2026-09-09 00:40:27
211
4whateverrr
Wander 🌼 :
He’s an icon na sa Makati. The LGU should have helped him na
2026-09-10 01:39:47
1
jasminnn.04
Jasmin :
LET’S GOOO
2026-09-10 12:31:03
1
nairoze_
NaiRoze✨ :
Up up up!
2026-09-10 11:32:55
2
frncsb_
𝗳𝗿𝗮𝗻𝗰𝗲𝘀 :
AHHH I WANNA VISIT READING CLUB 2000
2026-08-31 17:10:14
57
aanicoh
ja :
hearts
2026-09-09 06:27:11
90
makiiidesu
Greyisfyne :
Reposted 😭
2026-09-07 14:11:23
5
drlccm
powder :
LINK LINK LINK
2026-09-01 17:49:15
46
lig_ayaaah
Ligaya :
dapat eto tinutulungan ng gobyerno!
2026-09-08 13:11:11
203
baby.bunny573
Baby bunny :
coffee or tea
2026-09-08 12:41:30
67
dalealejandrov2
Dale Alejandro- Sanchez :
comment your favorite color
2026-08-31 12:55:45
1654
mareehaaaa
🕊️ :
Fave color:
2026-09-09 01:21:54
126
daneecadee
danee :
He’s the Dolly Parton of the Philippines 😍 Dito sa US, Dolly Parton has a foundation where they send free books to kids ages 1-5 years old. Sana the government can do this to help the kids read.
2026-08-31 13:37:14
3214
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Backpropagation is the algorithm that tells a neural network how each weight and bias contributed to its mistakes. 🧠 Here is exactly how it works: 1️⃣ Make a Prediction: The network processes the inputs using its current weights and biases. 2️⃣ Calculate Loss: A loss function measures how far the prediction is from the correct answer. 3️⃣ Propagate the Error: Starting from the output layer, the error flows backward through the network, computing how much each weight and bias contributed to the loss. 4️⃣ Compute the Gradient: This produces one derivative for every parameter, showing which direction reduces the loss the fastest. 5️⃣ Update the Parameters: Gradient descent nudges every weight and bias a small step in the direction that reduces the loss. 6️⃣ Repeat: The network repeats steps 1 through 5 over and over until its predictions become increasingly accurate. 📈 A few key things to know: ✅ Backpropagation computes the gradients—it does not update the weights itself. ✅ Gradient descent uses those gradients to actually update the weights and biases. ✅ The chain rule makes it possible to efficiently compute gradients for every parameter, even in very deep neural networks. Why it matters: ⚠️ Without backpropagation, modern neural networks wouldn't be able to learn from data. ⚠️ It makes training networks with thousands—or even millions—of parameters computationally feasible. #NeuralNetworks #Backpropagation #DeepLearning #AIEducation #MachineLearning
Backpropagation is the algorithm that tells a neural network how each weight and bias contributed to its mistakes. 🧠 Here is exactly how it works: 1️⃣ Make a Prediction: The network processes the inputs using its current weights and biases. 2️⃣ Calculate Loss: A loss function measures how far the prediction is from the correct answer. 3️⃣ Propagate the Error: Starting from the output layer, the error flows backward through the network, computing how much each weight and bias contributed to the loss. 4️⃣ Compute the Gradient: This produces one derivative for every parameter, showing which direction reduces the loss the fastest. 5️⃣ Update the Parameters: Gradient descent nudges every weight and bias a small step in the direction that reduces the loss. 6️⃣ Repeat: The network repeats steps 1 through 5 over and over until its predictions become increasingly accurate. 📈 A few key things to know: ✅ Backpropagation computes the gradients—it does not update the weights itself. ✅ Gradient descent uses those gradients to actually update the weights and biases. ✅ The chain rule makes it possible to efficiently compute gradients for every parameter, even in very deep neural networks. Why it matters: ⚠️ Without backpropagation, modern neural networks wouldn't be able to learn from data. ⚠️ It makes training networks with thousands—or even millions—of parameters computationally feasible. #NeuralNetworks #Backpropagation #DeepLearning #AIEducation #MachineLearning

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