Disclosure: when you buy through links on our site, we may earn an affiliate commission.

Applied Deep Learning with Keras

Solve complex real-life problems with the simplicity of Keras
4.6
4.6/5
(2 reviews)
38 students
Created by

9.2

CourseMarks Score®

9.0

Freshness

8.5

Feedback

9.5

Content

Platform: Udemy
Price: $11.99
Video: 10h 17m
Language: English
Next start: On Demand

Top Deep Learning courses:

Detailed Analysis

CourseMarks Score®

9.2 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

9.0 / 10
This course was last updated on 6/2020.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.5 / 10
We analyzed factors such as the rating (4.6/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.5 / 10
Video Score: 9.1 / 10
The course includes 10h 17m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 8 hours 47 minutes of 111 Deep Learning courses on Udemy.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

38 articles.
0 resource.
0 exercise.
0 test.

Table of contents

Description

Though designing neural networks is a sought-after skill, it is not easy to master. With Keras, you can apply complex machine learning algorithms with minimum code.
Applied Deep Learning with Keras starts by taking you through the basics of machine learning and Python all the way to gaining an in-depth understanding of applying Keras to develop efficient deep learning solutions. To help you grasp the difference between machine and deep learning, the course guides you on how to build a logistic regression model, first with scikit-learn and then with Keras. You will delve into Keras and its many models by creating prediction models for various real-world scenarios, such as disease prediction and customer churning. You’ll gain knowledge on how to evaluate, optimize, and improve your models to achieve maximum information. Next, you’ll learn to evaluate your model by cross-validating it using Keras Wrapper and scikit-learn. Following this, you’ll proceed to understand how to apply L1, L2, and dropout regularization techniques to improve the accuracy of your model. To help maintain accuracy, you’ll get to grips with applying techniques including null accuracy, precision, and AUC-ROC score techniques for fine tuning your model.
By the end of this course, you will have the skills you need to use Keras when building high-level deep neural networks.

About the Author

Ritesh Bhagwat has a master’s degree in applied mathematics with a specialization in computer science. He has over 14 years of experience in data-driven technologies and has led and been a part of complex projects ranging from data warehousing and business intelligence to machine learning and artificial intelligence. He has worked with top-tier global consulting firms as well as large multinational financial institutions. Currently, he works as a data scientist. Besides work, he enjoys playing and watching cricket and loves to travel. He is also deeply interested in Bayesian statistics.
Mahla Abdolahnejad is a Ph.D. candidate in systems and computer engineering with Carleton University, Canada. She also holds a bachelor’s degree and a master’s degree in biomedical engineering, which first exposed her to the field of artificial intelligence and artificial neural networks, in particular. Her Ph.D. research is focused on deep unsupervised learning for computer vision applications. She is particularly interested in exploring the differences between a human’s way of learning from the visual world and a machine’s way of learning from the visual world, and how to push machine learning algorithms toward learning and thinking like humans.
Matthew Moocarme is a director and senior data scientist in Viacom’s Advertising Science team. As a data scientist at Viacom, he designs data-driven solutions to help Viacom gain insights, streamline workflows, and solve complex problems using data science and machine learning.
Matthew lives in New York City and outside of work enjoys combining deep learning with music theory. He is a classically-trained physicist, holding a Ph.D. in Physics from The Graduate Center of CUNY and is an active Artificial Intelligence developer, researcher, practitioner, and educator.

You will learn

✓ Understand the difference between single-layer and multi-layer neural network models
✓ Use Keras to build simple logistic regression models, deep neural networks, recurrent neural networks, and convolutional neural networks
✓ Apply L1, L2, and dropout regularization to improve the accuracy of your model
✓ Implement cross-validate using Keras wrappers with scikit-learn
✓ Understand the limitations of model accuracy

Requirements

• Prior experience of Python programming and experience with statistics and logistic regression will help you get the most out of this course.Although not necessary, some familiarity with the scikit-learn library will be an added bonus.

This course is for

• If you have basic knowledge of data science and machine learning and want to develop your skills and learn about artificial neural networks and deep learning, you will find this course useful.

How much does the Applied Deep Learning with Keras course cost? Is it worth it?

The course costs $11.99. And currently there is a 87% discount on the original price of the course, which was $94.99. So you save $83 if you enroll the course now.
The average price is $15.1 of 111 Deep Learning courses. So this course is 21% cheaper than the average Deep Learning course on Udemy.

Does the Applied Deep Learning with Keras course have a money back guarantee or refund policy?

YES, Applied Deep Learning with Keras has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Applied Deep Learning with Keras course, but there is a $83 discount from the original price ($94.99). So the current price is just $11.99.

Who is the instructor? Is Packt Publishing a SCAM or a TRUSTED instructor?

Packt Publishing has created 2059 courses that got 58,562 reviews which are generally positive. Packt Publishing has taught 402,947 students and received a 4.0 average review out of 58,562 reviews. Depending on the information available, Packt Publishing is a TRUSTED instructor.
Tech Knowledge in Motion
Packt has been committed to developer learning since 2004. A lot has changed in software since then – but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.
With an extensive library of content – more than 4000 books and video courses -Packt’s mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what’s important to them now.
From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.

Packt Udemy courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.

9.2

CourseMarks Score®

9.0

Freshness

8.5

Feedback

9.5

Content

Platform: Udemy
Price: $11.99
Video: 10h 17m
Language: English
Next start: On Demand

Students are also interested in

Get this widget on your website (for course creators):

Applied Deep Learning with Keras rating
Copy this code and paste it to your website:
<a href="https://coursemarks.com/course/applied-deep-learning-with-keras/" target="_blank" title="Applied Deep Learning with Keras on Coursemarks.com"><img border="0" src="https://coursemarks.com/widget/94.svg" width="200px" alt="Applied Deep Learning with Keras rating"/></a>