Deep learning basics for beginners

Deep learning basics for beginners, available at Free, has an average rating of 4.1, with 13 lectures, based on 12 reviews, and has 1170 subscribers.

You will learn about I introduce a basic but important knowledge about deep learning You are going to understand how deep learning works You need approximately 2 weeks to finish this class I'll teach you knowledge that you have to know if you are interested in deep learning This course is ideal for individuals who are For anyone who is interested in deep learning It is particularly useful for For anyone who is interested in deep learning.

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Summary

Title: Deep learning basics for beginners

Price: Free

Average Rating: 4.1

Number of Lectures: 13

Number of Published Lectures: 13

Number of Curriculum Items: 13

Number of Published Curriculum Objects: 13

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

I introduce a basic but important knowledge about deep learning
You are going to understand how deep learning works
You need approximately 2 weeks to finish this class
I'll teach you knowledge that you have to know if you are interested in deep learning

Who Should Attend

For anyone who is interested in deep learning

Target Audiences

For anyone who is interested in deep learning

Welcome to my lecture! Nowadays, artificial intelligence is everywhere! You can see artificial intelligence, especially deep learning everywhere. Deep learning can draw beautiful art image , deep learning can make astonishing music, deep learning can even drive! I’m pretty sure that it’s okay to say nowadays are era of deep learning. And what if you can also dive into world of deep learning? As a graduate student, i always wanted to summarize what i learned and introduce it to people to help them understand deep learning more easily. Therefore, in this lecture, we are going to learn basic and really important knowledge that you have to know if you are beginner of deep learning. Before starting this lecture, you should know basic linear algebra, basic knowledge about probability and statistics and basic python programming in advance if you want more smooth understanding. After this lecture, you’ll be ready to dive into deep learning world that change your computer from just computer to tool for deep learning. I hope you to ask anything you want to ask me about lecture, or if there’s something missing or you want to know more, let me know without any hesitation. Again, welcome to my lecture everyone!

Course Curriculum

Chapter 1: Introduction to deep learning

Lecture 1: 소개

Lecture 2: What is deep learning?

Chapter 2: Knowledges you have to know

Lecture 1: Perceptron

Lecture 2: Perceptron 2 : Limitation of perceptron

Lecture 3: Perceptron to Deep learning : Linearity and nonlinearity

Lecture 4: Perceptron to Deep learning 2 : activation function

Lecture 5: Loss functions : How can we make neural network do what we want.

Lecture 6: Gradient decent : How can we make neural network do what we want

Lecture 7: Gradient vanishing and Gradient Exploding

Lecture 8: Activation function 2 : what is relu?

Lecture 9: Optimizers 1 : Is gradient decent perfect ?

Lecture 10: Underfitting and Overfitting : There's no perfect neural network.

Lecture 11: what you have to know : before starting neural network.

Instructors

Jiseong Hah
Udemy 강사

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3 stars: 5 votes
4 stars: 1 votes
5 stars: 6 votes

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