Learn Keras: Build 4 Deep Learning Applications

Learn Keras: Build 4 Deep Learning Applications, available at Free, has an average rating of 4.35, with 10 lectures, based on 357 reviews, and has 17967 subscribers.

You will learn about Simple implementation of convolutional neural networks, deep neural networks, recurrent neural networks, and linear regression Understanding of keras syntax Understanding of different deep learning algorithms This course is ideal for individuals who are Someone who wants to get into machine learning but feels overwhelmed by other tutorials or Someone who is interested in machine learning but doesn't know where to start It is particularly useful for Someone who wants to get into machine learning but feels overwhelmed by other tutorials or Someone who is interested in machine learning but doesn't know where to start.

Enroll now: Learn Keras: Build 4 Deep Learning Applications

Summary

Title: Learn Keras: Build 4 Deep Learning Applications

Price: Free

Average Rating: 4.35

Number of Lectures: 10

Number of Published Lectures: 10

Number of Curriculum Items: 10

Number of Published Curriculum Objects: 10

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Simple implementation of convolutional neural networks, deep neural networks, recurrent neural networks, and linear regression
Understanding of keras syntax
Understanding of different deep learning algorithms

Who Should Attend

Someone who wants to get into machine learning but feels overwhelmed by other tutorials
Someone who is interested in machine learning but doesn't know where to start

Target Audiences

Someone who wants to get into machine learning but feels overwhelmed by other tutorials
Someone who is interested in machine learning but doesn't know where to start

When I started learning deep learning, I had a hard time figuring out how everything worked. What library was the best for me? Which algorithms worked best for which data set? How could I know my model was accurate? I spent a lot of time on tutorials, courses and reading to try and answer these questions. In the end, I felt like the process I took to learn deep learning was too inefficient. That is why I created this course.

Learn Keras: Build 4 Deep Learning Applications is a course that I designed to solve the problems my past self had. This course is designed to get you up and running with deep learning as quickly as possible. We use keras in this course because it is one of the easiest libraries to learn for deep learning. Each video, we go over a different machine learning algorithm and its use cases. The four algorithms we focus on the most are:

1. Linear Regression

2. Dense Neural Networks

3. Convolutional Neural Networks

4. Recurrent Neural Networks

In conclusion, if you are looking at a quick intro into deep learning, this course is for you.

So what are you waiting for? Let’s get started!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Getting Set Up With Colab

Lecture 3: Github

Chapter 2: Traditional Machine Learning

Lecture 1: AI vs Machine Learning vs Deep Learning

Lecture 2: What Is Linear Regression?

Lecture 3: Linear Regression in Keras

Chapter 3: Neural Networks

Lecture 1: Keras Deep Neural Network (DNN)

Lecture 2: Keras Convolutional Neural Network (CNN)

Lecture 3: Keras Recurrent Neural Network (LSTM)

Lecture 4: Want To Watch More Free Programming Content?

Instructors

Adam Eubanks
Self Taught Programmer And Learning Enthusiast

Rating Distribution

1 stars: 8 votes
2 stars: 14 votes
3 stars: 67 votes
4 stars: 125 votes
5 stars: 143 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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