@martuchizzini: Como están? 🔥 #fyp #foryou #parati #foryourpage #dance #dancer #twerk

Martu Chizzini

Open In TikTok:

Region: CL

Sunday 11 October 2020 22:37:52 GMT

2432523

230993

1056

8434

Music

Download

No Watermark .mp4 (3.26MB) No Watermark(HD) .mp4 (3.26MB) Watermark .mp4 (3.27MB) Music .mp3

Comments

Mike_OnTiktok :

she knew exactly what she was doing

2020-10-12 02:14:07

185

Fnnfkcjcncn Cjcjncnv :

THAT THANG WAS VIBRATING LIKE A NOKIA 3310...

2020-10-12 02:27:45

335

WILLY :

Cómo dijo alguien: una sentada de esas y se te reinicia la vida 😳😳

2020-10-11 23:37:43

31

luv.yaz :

WAIT, she looks like Noah schnapp a bit 😳😂

2020-10-13 01:45:07

27

cultofdrift :

Mein ganzer stolz

2020-11-08 02:33:40

13

matt :

les autre le fond bien toi tu fais plus que abuser

2020-10-12 03:00:32

43

M A U R :

Es la hija de alexis texas

2020-10-11 23:39:01

96

co ty gadasz :

pov :jesteś od polubionych jakiegoś dziwnego typka

2021-05-17 20:52:19

11

Ojeda Dayerlin :

🥰como haces el paso el conejo no puedo ayudame🥰

2020-10-11 22:59:32

18

A.12 :

اللهم احرمني لذه معصيتك و ارزقني لذة طاعتك

2020-10-12 02:34:25

27

Julio :

un senton ella y se te reinicia la vida 😳

2020-10-11 23:32:57

149

nothing :

جسمي احلى

2020-10-12 00:51:29

6

cemre :

Ilk Türk 🥺😌

2020-12-02 21:09:50

10

Loris :

lève tes yeux

2020-10-14 09:07:25

12

Noname :

وردي وردي 🥰🥰🥰🥰🥰 روز

2020-10-11 23:11:54

9

RÃ :

كمممميية للححمممم

2020-10-12 03:21:41

7

nicmoons :

MANTAP AMJINC

2020-10-12 12:34:30

34

diba :

belom tgl 13

2020-10-12 08:19:18

5

John_315 :

I swear one of them is about to pop out

2020-10-15 05:44:17

11

Fitterman :

The very best version of this trend, you can really move it

2020-10-15 22:47:41

7

da_mo10 :

وردي 😂😂😂

2020-10-12 01:48:42

3

isa :

güzelsin

2020-12-06 04:57:32

3

vdvlka :

Русские

2020-10-12 02:24:21

1

Emanuel Serrano :

yo muy bien y usted ya comió.?

2020-10-12 01:28:33

3

Yorichii :

gg nn

2020-11-06 18:08:01

3

To see more videos from user @martuchizzini, please go to the Tikwm homepage.

Other Videos

@🐙👑 ⓡŞ Ŧυ𝕙𝔦Ⓝ ⛵🐠

@🐙👑 ⓡŞ Ŧυ𝕙𝔦Ⓝ ⛵🐠

goyang dayung🤙😎 #dikaprst🎟

goyang dayung🤙😎 #dikaprst🎟

মেনশন দেন আপনার বন্ধু কে 😂😂(4k memes) #shorts #comedy #cartoon #animation

মেনশন দেন আপনার বন্ধু কে 😂😂(4k memes) #shorts #comedy #cartoon #animation

➡️ Part 10 of learning ML code from scratch: How does an AI see things? Step 1, pixels. Every picture is a grid of pixels, and every pixel is one number for its brightness, 0 for black and 1 for white. Ours is 16 by 16. Step 2, the input. Put the rows one after another and you get 256 numbers. That list is everything the model ever sees of the picture. Step 3, ten neurons, one for every digit. Each one is the neuron from part 2. It multiplies every pixel by its own weight and adds everything up into one score. For our eight, the eight neuron scores 5.66. Step 4, softmax turns the ten scores into chances that add up to 100 %. The eight gets 90 %, and the zero comes second with 4 %. Step 5, learning. All 2,560 weights start at zero, so every digit gets 10 %. Then the model studies 3,000 example digits in three rounds, and after each one the blame from part 9 nudges every weight a tiny bit. Step 6, the best part. Put the 256 weights of one neuron back into the shape of the picture and you can see what it learned to look for. Green means a bright pixel there counts for the digit, red means it counts against it. The zero neuron learned a green ring and a red middle. Step 7, why the red matters. On the ring alone, the zero neuron would score 5.85 for our eight and beat the eight neuron. The crossing of the eight lands on the red middle and costs it 3.22 points. Switch the red off and all 50 eights in the test get called a zero. The result: 490 of 500 digits it had never seen, read correctly, with nothing but multiplication and addition. Half of the 10 mistakes are fours and nines mixed up. Real vision models stack many layers of these. The first layers find edges and small strokes, and the deeper ones build loops, faces and cars. Every number in the video comes from a real run of the code, and the video checks its own claims before it renders. The scores must match to nine decimal places, and the 490 of 500 and the 50 of 50 must match exactly, otherwise nothing renders. #machinelearning #computervision #neuralnetworks #python #coding

➡️ Part 10 of learning ML code from scratch: How does an AI see things? Step 1, pixels. Every picture is a grid of pixels, and every pixel is one number for its brightness, 0 for black and 1 for white. Ours is 16 by 16. Step 2, the input. Put the rows one after another and you get 256 numbers. That list is everything the model ever sees of the picture. Step 3, ten neurons, one for every digit. Each one is the neuron from part 2. It multiplies every pixel by its own weight and adds everything up into one score. For our eight, the eight neuron scores 5.66. Step 4, softmax turns the ten scores into chances that add up to 100 %. The eight gets 90 %, and the zero comes second with 4 %. Step 5, learning. All 2,560 weights start at zero, so every digit gets 10 %. Then the model studies 3,000 example digits in three rounds, and after each one the blame from part 9 nudges every weight a tiny bit. Step 6, the best part. Put the 256 weights of one neuron back into the shape of the picture and you can see what it learned to look for. Green means a bright pixel there counts for the digit, red means it counts against it. The zero neuron learned a green ring and a red middle. Step 7, why the red matters. On the ring alone, the zero neuron would score 5.85 for our eight and beat the eight neuron. The crossing of the eight lands on the red middle and costs it 3.22 points. Switch the red off and all 50 eights in the test get called a zero. The result: 490 of 500 digits it had never seen, read correctly, with nothing but multiplication and addition. Half of the 10 mistakes are fours and nines mixed up. Real vision models stack many layers of these. The first layers find edges and small strokes, and the deeper ones build loops, faces and cars. Every number in the video comes from a real run of the code, and the video checks its own claims before it renders. The scores must match to nine decimal places, and the 490 of 500 and the 50 of 50 must match exactly, otherwise nothing renders. #machinelearning #computervision #neuralnetworks #python #coding

About

Robot
API

Legal

Privacy Policy