Empeds Casul
Region: PH
Saturday 02 August 2025 10:41:50 GMT
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ghost :
I'M SO EARLY THERE'S NO LIKES YET 💔
2025-08-02 10:45:35
3
I’m_quitr5e6 :
I think buchayna next die
2025-08-02 10:58:48
0
Randy_Dump :
Waiting For Episode 2 Sneak Peek 👀👀
2025-08-02 11:34:35
1
Buz :
Ngayon Yung Ep 2
2025-08-02 11:31:25
0
jelly.ffx :
Kaylan ilalabas yung episo 2 ng school horror story
2025-08-02 12:34:43
2
Realyn Javier :
AshleYColeenJCasquio😁😁🥰🙏🤩
2025-09-23 12:40:59
0
로샨빈스 👾 :
early
2025-08-02 10:45:05
1
J :
NASAAN SI BETH LOGAN🥺
2025-08-02 21:46:49
0
°𓆡.•𓍯° ©hí Dũng★ ᝰ.ᐟ ִ✧* :
slay girl 360🥰🥰🥰🥰
2025-08-06 02:38:30
0
robertcamposano80 :
😂
2025-10-11 13:44:28
0
Maryjane aranzanso :
🥰🥰🥰
2025-10-25 04:58:37
0
Deadmeqt :
OMGG NGAYON EP 2?
2025-08-02 11:25:48
9
𝒮 :
EARLYYY FOWLER
2025-08-02 11:00:08
4
L0UR3D :
earlyyyy
2025-08-02 11:06:13
2
L0UR3D :
hahah nag aabang parin sko
2025-08-02 11:08:02
2
Martin :
Helicopter Divas 🚁🔥
2025-08-02 12:07:02
2
`Ñißßles~ ` ° ^ ° ` :
tut kung paano ang kamay😭
2025-08-02 11:05:50
1
Empeds Casul Fan (Nikolai) :
My Divas
2025-08-02 11:29:08
1
๑•͈ᴗ•͈๑yuro๑•͈ᴗ•͈๑ :
unnie Fowler nag babalik
2025-08-02 11:19:20
1
renxzy :
EARLYYY
2025-08-02 11:20:36
1
Will_Dump :
Si Unnie Siguro Ang Master Ng Dancer
2025-08-02 11:24:08
1
ako to si jairus :
Cathy o tenco is the diva
2025-08-02 11:28:09
1
asprisha_ :
is that player 360♥️
2025-08-02 12:05:12
1
🌊🌪️Miko🔥🌎 :
our diva
2025-08-02 12:14:35
1
𝕥ꪖꪗ☄️ :
O KATSEYE PRECISA VER ISSO
2025-08-02 15:49:43
1
FAIZANPAUl :
🤣🤣
2025-08-05 00:28:31
1
R🔹☃️ :
2025-08-04 10:26:49
1
kiyoshii :
oh my diba
2025-08-03 03:02:01
1
kiyoshii :
slay girl 😝💅🏻
2025-08-03 03:02:22
1
vc_gnda :
EARLY!!
2025-08-02 10:46:01
1
CAS P JAM :
slay
2025-08-02 10:46:26
1
🇻🇦jerico :
early
2025-08-02 10:46:48
1
ella:3 :
sobrang early!!!
2025-08-02 10:46:12
1
空 skyler :
omgg early
2025-08-02 10:48:56
1
🪨𝓑𝓵𝓲𝓷𝓭~𝓑𝓪𝓷𝓭𝓲𝓽🪨 :
Bago maging viral I’m here
2025-08-02 10:49:48
1
🪽 :
early erm
2025-08-02 10:50:14
1
kalbo:) :
hi po
2025-08-02 10:50:18
1
Noah the Contortion :
Early bigyan ng rawr RAWR
2025-08-02 10:53:42
1
jelly.ffx :
EARLY!
2025-08-02 10:55:11
1
𝓢𝓱𝓪𝓭𝓸𝔀 𝓶𝓲𝓵𝓴 ·ࡇ· :
EARLY
2025-08-02 10:55:14
1
{Yannah15564} :
@wheizelleanneubal
2025-08-07 08:04:37
0
Jelian Rose Salgado :
🥰🥰🥰
2025-08-07 11:33:50
0
Alvin James Mape :
🥰🥰🥰
2025-08-07 01:05:51
0
cARTer_CoOleE195 :
ang dami mong ganap Unnie Fowler,,Hindi kapanga nakakapahinga matapos manalo Ng Squid Game at ayon lumalaban kana namn,,btw,,STILL PROUF OF U💓💓🥰😍
2025-08-08 08:37:05
0
Jelian Rose Salgado :
❤❤❤
2025-08-07 11:33:52
0
Seth Timothy Catacutan :
😂😂😂
2025-08-07 14:05:32
0
loreign :
na mamansin bato?
2025-08-08 00:28:15
0
Lyn :
🙏🙏🙏
2025-08-06 09:39:57
0
🇹🇷 :
Mizi?
2025-08-08 14:18:23
0
Mary ann Madrid :
😳😳😳
2025-08-06 12:37:50
0
Julianna🤍💜💙🩵🩷 :
🥰🥰🥰
2025-08-06 11:06:51
0
🍀M🍀 :
😁😁😁
2025-08-06 09:52:16
0
To see more videos from user @empedscasul, please go to the Tikwm
homepage.
![In Machine Learning, sometimes the built-in transformers (like StandardScaler or OneHotEncoder) aren’t enough. What if you want to apply your own math function to features? 🤔 👉 That’s where 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫 comes in 🚀 It lets you apply custom transformations (NumPy, Pandas, or your own function) directly inside ML pipelines. ⸻ 🔹 Common Types of FunctionTransformers: 1️⃣ Log Transformation → Handles skewed data, makes distribution more normal. 🔸 Example: FunctionTransformer(np.log1p) 2️⃣ Square / Power Transformation → Useful for polynomial-like effects. 🔸 Example: FunctionTransformer(np.square) 3️⃣ Scaling / Normalization (Custom) → Normalize features manually. 🔸 Example: FunctionTransformer(lambda x: x / np.max(x)) 4️⃣ Feature Engineering → Create ratios, percentages, or domain-specific features. 🔸 Example: FunctionTransformer(lambda x: x[:,0] / (x[:,1]+1)) ⸻ ⚡ Why it’s powerful: ✅ Works inside Pipelines ✅ Flexible & customizable ✅ Great for feature engineering ⚠️ Needs careful design — a wrong function can ruin the model! ⸻ 💡 Key Takeaway: FunctionTransformer = Apply custom math/logic to your features inside ML pipelines. A must-have tool for advanced preprocessing & feature engineering 🔥 #️⃣ #FunctionTransformer #MachineLearning #DataScience #100DaysOfML #AIForBeginners #mljourney](/video/cover/7545115865428004104.webp)
