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AI Development

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Deep Learning & Machine Learning

Deep Learning with Keras

Understand the principles of deep learning and use Keras to simplify the complexity of building and training neural networks using models, layers, and optimization techniques.

16 learners are taking this course

  • jikim1770
이론 실습 모두
딥러닝입문
인공지능기초수학
케라스
Deep Learning(DL)
Keras
CNN
RNN

What you will learn!

  • What is Deep Learning?

  • Mathematics for Deep Learning

  • Getting started with neural networks

  • Understanding multilayer neural networks

  • Main Keras syntax

  • Understanding Convolutional Neural Networks

  • Understanding Recurrent Neural Networks

Dive into the world of Keras, where you can understand deep learning algorithms and implement them concisely. Easily implement the models you need.

Learning Content

Section (1) What is Deep Learning?

We explain the background of the emergence of deep learning and introduce a general deep learning learning method.

Section (2) Mathematics for Deep Learning

Explains the gradient descent algorithm using differentiation and the process for finding optimal weights.

Section (3) Starting the Neural Network

We will explain the neural network architecture and implement the neural network using Python and Keras.

Section (4) Understanding Multilayer Neural Networks

We explain the process of transitioning from single-layer to multi-layer and introduce the learning process of multi-layer neural networks.

Section (5) Main Keras Grammar

Using visual aids like class screenshots, example images, and diagrams can make your introduction more engaging.

Section (6) Understanding Convolutional Neural Networks

We will explain convolutional neural networks (CNNs), which are important in the field of vision, and implement convolutional neural networks using Keras.

Section (7) Understanding Recurrent Neural Networks

We will explain recurrent neural networks (RNNs), which are important in the field of natural language processing, and implement them using Keras.

Things to note before taking the course

Practice environment

  • Operating System and Version (OS): Windows 10,11

  • Editing tools: Windows Anaconda, Jupyter Notebook

  • Compiler: Python 3.8

Learning Materials

  • Learning materials provided in PDF format

  • During class, we use PPT to write on the board and share it as class materials (PDF).

Player Knowledge and Precautions

  • Prerequisites for this course: Python basics

  • This lecture video specifications: FPS-60, resolution-1280*720, audio sample rate-44,100

  • Please feel free to ask questions, and the lectures may be revised as new techniques emerge.

  • The learning materials distributed during lectures are for class use only and unauthorized distribution is prohibited.

Recommended for
these people

Who is this course right for?

  • Anyone curious about the principles of deep learning

  • Anyone who wants to create a model using Keras

  • For those who use Keras but are curious about its internal structure

Need to know before starting?

  • Python Basics

Hello
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703

Learners

66

Reviews

11

Answers

4.9

Rating

9

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강의문의 : jikim@imguru.co.kr

Curriculum

All

45 lectures ∙ (13hr 47min)

Course Materials:

Lecture resources
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$68.20

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