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Deep Learning with Python and Keras

Understand and build Deep Learning models for images, text and more using Python and Keras
4.3
4.3/5
(3,002 reviews)
22,631 students
Created by

8.0

Classbaze Grade®

5.8

Freshness

8.4

Popularity

9.3

Material

Understand and build Deep Learning models for images
Platform: Udemy
Video: 9h 56m
Language: English
Next start: On Demand

Best Deep Learning classes:

Classbaze Rating

Classbaze Grade®

8.0 / 10

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

Freshness

5.8 / 10
This course was last updated on 12/2018.

Course content can become outdated quite quickly.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.

Popularity

8.4 / 10
We analyzed factors such as the rating (4.3/5) 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.

Material

9.3 / 10
Video Score: 9.1 / 10
The course includes 9h 56m 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 18 minutes of 153 Deep Learning courses on Udemy.
Detail Score: 9.3 / 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:

6 articles.
0 resource.
0 exercise.
0 test.

In this page

About the course

This course is designed to provide a complete introduction to Deep Learning. It is aimed at beginners and intermediate programmers and data scientists who are familiar with Python and want to understand and apply Deep Learning techniques to a variety of problems.
We start with a review of Deep Learning applications and a recap of Machine Learning tools and techniques. Then we introduce Artificial Neural Networks and explain how they are trained to solve Regression and Classification problems.
Over the rest of the course we introduce and explain several architectures including Fully Connected, Convolutional and Recurrent Neural Networks, and for each of these we explain both the theory and give plenty of example applications.
This course is a good balance between theory and practice. We don’t shy away from explaining mathematical details and at the same time we provide exercises and sample code to apply what you’ve just learned.
The goal is to provide students with a strong foundation, not just theory, not just scripting, but both. At the end of the course you’ll be able to recognize which problems can be solved with Deep Learning, you’ll be able to design and train a variety of Neural Network models and you’ll be able to use cloud computing to speed up training and improve your model’s performance.

What can you learn from this course?

✓ To describe what Deep Learning is in a simple yet accurate way
✓ To explain how deep learning can be used to build predictive models
✓ To distinguish which practical applications can benefit from deep learning
✓ To install and use Python and Keras to build deep learning models
✓ To apply deep learning to solve supervised and unsupervised learning problems involving images, text, sound, time series and tabular data.
✓ To build, train and use fully connected, convolutional and recurrent neural networks
✓ To look at the internals of a deep learning model without intimidation and with the ability to tweak its parameters
✓ To train and run models in the cloud using a GPU
✓ To estimate training costs for large models
✓ To re-use pre-trained models to shortcut training time and cost (transfer learning)

What you need to start the course?

• Knowledge of Python, familiarity with control flow (if/else, for loops) and pythonic constructs (functions, classes, iterables, generators)
• Use of bash shell (or equivalent command prompt) and basic commands to copy and move files
• Basic knowledge of linear algebra (what is a vector, what is a matrix, how to calculate dot product)
• Use of ssh to connect to a cloud computer

Who is this course is made for?

• Software engineers who are curious about data science and about the Deep Learning buzz and want to get a better understanding of it
• Data scientists who are familiar with Machine Learning and want to develop a strong foundational knowledge of deep learning

Are there coupons or discounts for Deep Learning with Python and Keras ? What is the current price?

The course costs $19.99. And currently there is a 84% discount on the original price of the course, which was $124.99. So you save $105 if you enroll the course now.
The average price is $16.2 of 153 Deep Learning courses. So this course is 23% more expensive than the average Deep Learning course on Udemy.

Will I be refunded if I'm not satisfied with the Deep Learning with Python and Keras course?

YES, Deep Learning with Python and 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 financial aid for this course?

Currently we could not find a scholarship for the Deep Learning with Python and Keras course, but there is a $105 discount from the original price ($124.99). So the current price is just $19.99.

Who will teach this course? Can I trust Data Weekends?

Data Weekends has created 3 courses that got 3,041 reviews which are generally positive. Data Weekends has taught 23,863 students and received a 4.3 average review out of 3,041 reviews. Depending on the information available, we think that Data Weekends is an instructor that you can trust.
Learn the essentials of Data Science in just one weekend
Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science, Machine Learning and Python Programming. He has publications and patents in various fields such as microfluidics, materials science, and data science. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Training and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, McKinsey and many more. Feel free to check out the website link to find out more information about training offerings.
Browse all courses by on Classbaze.

8.0

Classbaze Grade®

5.8

Freshness

8.4

Popularity

9.3

Material

Platform: Udemy
Video: 9h 56m
Language: English
Next start: On Demand

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