Этот курс научит вас использовать Keras, API нейронной сети, написанный на Python и интегрированный с TensorFlow. Мы научимся подготавливать и обрабатывать данные для искусственных нейронных сетей, строить и обучать искусственные нейронные сети с нуля, строить и обучать сверточные нейронные сети (CNN), выполнять тонкую настройку и передавать обучение и многое другое! ⭐️🦎 СОДЕРЖАНИЕ КУРСА 🦎⭐️ ⌨️ (00:00:00) Добро пожаловать на этот курс ⌨️ (00:00:16) Введение в курс Keras ⌨️ (00:00:50) Предварительные требования к курсу ⌨️ (00:01:33) DEEPLIZARD Deep Learning Путь ⌨️ (00:01:45) Ресурсы курса ⌨️ (00:02:30) О Keras ⌨️ (00:06:41) Keras с TensorFlow — обработка данных для обучения нейронной сети ⌨️ (00:18:39) Создание искусственного Нейронная сеть с API Keras от TensorFlow ⌨️ (00:24:36) Обучение искусственной нейронной сети с API Keras от TensorFlow ⌨️ (00:30:07) Создание проверочного набора с API Keras от TensorFlow ⌨️ (00:39:28) Прогнозы нейронной сети с API Keras от TensorFlow ⌨️ (00:47:48) Создание матрицы путаницы для прогнозов нейронных сетей ⌨️ (00:52:29) Сохранение и загрузка модели с API Keras от TensorFlow ⌨️ (01:01:25) Подготовка изображения для CNN с Keras API от TensorFlow ⌨️ (01:19:22) Создание и обучение CNN с помощью Keras API от TensorFlow ⌨️ (01:28:42) Прогнозирование CNN с помощью Keras API от TensorFlow ⌨️ (01:37:05) Создание точно настроенной нейронной сети с TensorFlow Keras API ⌨️ (01:48:19) Обучение точно настроенной нейронной сети с помощью TensorFlow Keras API ⌨️ (01:52:39) Прогнозирование с помощью точно настроенной нейронной сети с помощью TensorFlow Keras API ⌨️ (01:57:50) MobileNet Классификация изображений с помощью TensorFlow Keras API ⌨️ (02:11:18) Обработка изображений для точной настройки MobileNet с помощью TensorFlow Keras API ⌨️ (02:24:24) Тонкая настройка MobileNet на пользовательском наборе данных с помощью TensorFlow Keras API ⌨️ (02:38) :59) Увеличение данных с помощью TensorFlow’ Keras API ⌨️ (02:47:24) Коллективный разум и DEEPLIZARD HIVEMIND ⭐️🦎 РЕСУРСЫ СООБЩЕСТВА DEEPLIZARD 🦎⭐️ 👉 Ознакомьтесь с постом в блоге и другими ресурсами для этого курса: 🔗

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deeplizard
deeplizard
5 months ago

Hi everyone! Hope you all learn and gain from this course! Come check out the other deep learning courses available on our channel! ❤️🦎

A Tiny Blues
A Tiny Blues
5 months ago

darkmode pls

Ashwani Kumar
Ashwani Kumar
5 months ago
Ash
Ash
5 months ago

I am getting validation accuracy on the 1st data set that is clinical trial as , 64.84% exactly for 6 epochs and then jumps to 100%. no stepwise increase . Any idea why?. Rerunning didn't change anything

me
me
5 months ago

I can't concentrate because I'm looking at your (beautiful) freckles 🙂

Leonard Wissner
Leonard Wissner
5 months ago

Thanks!

Anthony Ryan
Anthony Ryan
5 months ago

Clear communicator. Interesting lessons. Good vid

ansuman samal
ansuman samal
5 months ago

I guess i am learning keras now…

Sushen Sharma
Sushen Sharma
5 months ago
علیرضا قنبری
علیرضا قنبری
5 months ago

Hello, can you put your personal github address in the description section of the YouTube channel?

Alexis Gaillard
Alexis Gaillard
5 months ago

when i use fit focntion it's return nen

Burak Duran
Burak Duran
5 months ago

As I go through some readings, they say that the test folder should not contain several sub-folders and the images under test should not be labeled. In my cases, I am having some IndexError but still I could not figure it out. Anyone has any idea? I have basically 4 classes and I am creating for different sub-folders by labeling the images and files under test file. In this video, she does the same things. Interestingly, when I run model.fit, it says "IndexError: index 1 is out of bounds for axis 2 with size 1"

amna batool
amna batool
5 months ago

Hey, can you please tell how to assign sample_weights in model.compile for imbalanced data?

T V
T V
5 months ago

Thankssssssssssssssssss!!!!!!!!

T V
T V
5 months ago

Thx

Being Data Scientist
Being Data Scientist
5 months ago

HI Please update the code:

model.fit(x = train_batches, validation_data = valid_batches, epochs = 10, verbose = 2) # conv fit

Error: TypeError: __array__() takes 1 positional argument but 2 were given

Jsan Sandi
Jsan Sandi
5 months ago

Not only was I not distracted by her beautifulness, I was actually able to understand everything she said. Thank you!

Paul Dacus
Paul Dacus
5 months ago

02:46:04 Nice.

MegaOjetemoreno
MegaOjetemoreno
5 months ago

I guess I am sick but… Am I the only that sees the weird vibes of the set up? why the bed? Is this made on purpose?

Sumo Cum Loudly
Sumo Cum Loudly
5 months ago

The machine learning tutorial space is a literal landfill of garbage, thousands of slightly different versions of this and that.

Given the fact that these models can be created with 10 lines of code, you would think there would be a really simple start to finish showing data to results in 10 mins, but all there is is 3 hour mess videos like this.

raghav bhardwaj
raghav bhardwaj
5 months ago

I cant describe in words how much this video helped me with my research project! You are a great teacher, Thankyou so much!

TwixWyd
TwixWyd
5 months ago

Nice

Drow0Ranger
Drow0Ranger
5 months ago

Hi Mandy, I tried training neural network for the clinical trials example @28:47. I am getting Nan for loss and 0.5 for accuracy. I ran the exact lines of code you did. What is the issue? BTW, I am not using the three lines of code to use the GPU.

Rachel Chu
Rachel Chu
5 months ago

too much repeated content, but good side of repeat is it enforces memory. so overall pretty good

Tony Cardinal
Tony Cardinal
5 months ago

There's a great book out there that does an awesome job at explaining every single line of python code for deep learning and artificial intelligence. It's called "Artificial Intelligence and Deep Learning with Python Every Line of Code Explained "

BrasW
BrasW
5 months ago

Abella dangers

Denv
Denv
5 months ago

The bed as a background for DL tutorial is not the best idea.

Priyanshu Raj
Priyanshu Raj
5 months ago

@ 1:25:00 I am getting error Error "when checking input: expected conv2d_3_input to have shape (224, 224, 3) but got array with shape (244, 244, 3)" How to resolve this?

m mo
m mo
5 months ago

Hi, I'm new to the subject and eager to understand. ☺️ Watching the episode Train an Artificial Neural Network (circa 29:00) and I understand the training but don't really understand whether the model there was just trained "theoretically", so to say, or was there any actual data input present, as I don't remember that being discussed. I understand that information is being added gradually and I can live with not knowing everything at once 😄, but this seems important – can I run a model without any actual input to check how it works or is it just not being shown. Sorry if I'm misunderstanding everything 😄😅

suriya rs
suriya rs
5 months ago

Why the test samples has to be in the same format as train samples ?
Test samples can be random nah

mudabir ahmad
mudabir ahmad
5 months ago

Such a detailed and amazingly designed course. Covered every question I had in mind!.

Nicky Reds
Nicky Reds
5 months ago

Finally, a southern accent.

Mozart Antonio
Mozart Antonio
5 months ago

awesome quality video!!

Shiesty Savage 🥶👌
Shiesty Savage 🥶👌
5 months ago

Crossentropy

Mohammed Zia
Mohammed Zia
5 months ago

One of the best videos on Keras Deep Learning. Thanks for your wonderful teaching.

Takauya Murengwa
Takauya Murengwa
5 months ago

Dear Lady DeepLizard,
Thank you so much for the energy, time and thought you've putting this course! I have benefited a lot from your channel,

John Ross
John Ross
5 months ago

Thanks for a well prepared, well organized, professional presentation. GREATLY appreciated

pooya
pooya
5 months ago

Where can I download resources?

Zen ツ Master
Zen ツ Master
5 months ago

I love her deep freckles. 😄

mathew tedder
mathew tedder
5 months ago

I am not sure why but… somehow I feel like she is an AI.

Jacob Perschbacher
Jacob Perschbacher
5 months ago

"alright, that's it for the manual labor" at the one hour mark haha… i love it.

Maitreya Kanitkar
Maitreya Kanitkar
5 months ago

completely off topic, but mandy looks a lot like Gal Gadot. The course was awesome though.

Candy Kane
Candy Kane
5 months ago

Can't get the fine tuning to work. The accuracy and validation accuracy are quite high for the vgg16 model but when I get it to predict and plug it into the confusion matrix plotting function, it shows something completely off.

Drone256
Drone256
5 months ago

This tutorial is great but it's too focused on image data.

lorian jan
lorian jan
5 months ago

hi, ho do i change the input shape in vgg16?

Семён Семёныч
Семён Семёныч
5 months ago

Awesome, Mandy you rock

حكيم
حكيم
5 months ago

ثثثث ياسبوكة

LOGAN ART
LOGAN ART
5 months ago

u accetly look like abbela danger 1000000000000000%

Σπυρος Γιαννας
Σπυρος Γιαννας
5 months ago

Sorry for being little critical here even though it's helpful tutorial some things were just left hanging…

To the people that actually try to repeat the tutorial (because I don't think there many) I have to say you have to use your logic to figure things out and not take everything for granted because it will not work she just messed up some parts…
For example: when she shuffles the data they have to be shuffled in union with the answers because your model will be accurate in training but 50% accurate on the unseen answers since it's like you lost the answers… Don't ask me if I messed that part by blindly following and wasting half an hour…
So you have to find your way to do this she leaves that part out and I don't know how she gets results…
Maybe keras at the time did it by default and currently not? Or I missed something idk…
Also some of the functions don't work if you follow on your computer's compiler… Reshape, Radom. I mean they work but you have to specify the module. I know some python masters will say you just don't know how to use python modules and I agree but this tutorial is not for the people knowing only less than two programming languages and starting out with keras.
Sorry, but it still helped to start somehow but it wasn't the best experience…

Adam Rohde
Adam Rohde
5 months ago

Thanks!

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