Data Weekends
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.
Instructor Details
Courses : 1
Specification: Deep Learning with Python and Keras
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9 reviews for Deep Learning with Python and Keras
Add a review
| Price | $14.99 |
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| Provider | |
| Duration | 10 hours |
| Year | 2018 |
| Level | Intermediate |
| Language | English ... |
| Certificate | Yes |
| Quizzes | No |
$14.99
Victor Wong –
Clear Explanation of concept, practical coding, and nice suggestion of model optimization. To completely follow the equation, some prior basic knowledge of math is needed.
Philip Oedi –
inhalte sehr gut, L sungen zu manchen Aufgaben fehlen leider
Anders Albert –
The course gives a solid introduction to keras, and the theoretical concepts are nicely explained along without the authors being afraid of going into the math. In addition, the lecture has made some small exercises to help consolidate the knowledge. What annoys me is that this course was made in 2017, and now 2020 the solutions to the four last exercises are still marked as coming soon. In addition, I would like to mention that the lecture makes the dummy variable trap in section 3, which makes me question his expertise.
Kunshan Yin –
Nice way to see how to apply NN framework to the common machine learning methods such ols , logistic regression.
Ryan Keck –
The material of the course was pretty good. However, it doesn’t look like questions have been answered by the instructor in the last year. The course also seems kind of unfinished. A few of the solutions do not have videos at the end, it just says coming soon or something. Regarding the exercises, I’m a little bit torn. I wish they were a little bit more specific, since I’m mostly just trying to get an understanding of the code and how to make things run. That being said, if you’ve never had to fiddle with things to make them work, the exercises will be a painful but worthwhile experience. Essentially, the exercises are probably a lot closer to what you’ll see in the real world. Most other courses hold your hand through the exercises, but not here. This is probably not a good first course in machine learning, but if you’ve gone through another course or two, this should add on to the foundation really well. The course has things I didn’t see in other courses. I highly recommend looking at the course at some point, but I would wait for a sale or something, I can’t recommend at full price.
Guilherme Mendon a Freire –
Nice. So far.
Viktor Semenov –
Very nice course. Well designed and very well thought. I would put 5 star, but the course a little bit not finished
Matthew Afsahi –
I have got this course because I thought Jose will be teaching this course as he is very good at teaching and explaining the materials, unfortunately this course was not that useful for me and my learning progress.
Allan Angulo –
Buena elecci n, hacen faltan unas lecciones.