jcg
Comprehensive Course Description:
Convolutional Neural Networks (CNNs) are considered as game–changers in the field of computer vision, particularly after AlexNet in 2012. And the good news is CNNs are not restricted to images only. They are everywhere now, ranging from audio processing to more advanced reinforcement learning (i.e., Resnets in AlphaZero). So, the understanding of CNNs becomes almost inevitable in all the fields of Data Science. Even most of the Recurrent Neural Networks rely on CNNs these days. So, keeping all these concerns in parallel, with this course, you can take your career to the next level with an expert grip on the concepts and implementations of CNNs in Data Science.
The course ’Mastering Convolutional Neural Networks, Theory and Practice in Python‘ is crafted to reflect the in–demand skills in the marketplace that will help you in mastering the concepts and methodology with regards to Python. The course is:
Easy to understand.
Exhaustive.
Expressive.
Practical with live coding.
Rich with state–of–the–art and recently discovered CNN models by the champions in this field.
How is this course different?
This course has been designed for beginners. However, we will go far deep gradually.
Also, this course is a quick compilation of all the basics, and it encourages you to press forward and experience more than what you have learned. By the end of every module, you will work on the assigned Homework/tasks/activities, which will evaluate / (further build) your learning based on the previous concepts and methods. Several of these activities will be coding–based to get you up and running with implementations.
Specification: Deep Learning CNN: Convolutional Neural Networks with Python
|
15 reviews for Deep Learning CNN: Convolutional Neural Networks with Python
Add a review
| Price | $14.99 |
|---|---|
| Provider | |
| Duration | 15.5 hours |
| Year | 2022 |
| Level | All |
| Language | English ... |
| Certificate | Yes |
| Quizzes | No |
$14.99
Peter van der Post –
Clear explanation of overview of the subjects in the course. Interesting subjects for me and I think the right level for me to take the course ( I ve heard about CNN ). Sometimes a little too slow pace, however I m not a complete beginner. Some spoken words are repeated too much, like so… . Thus far I m interested and happy. Let s continue.
Yoiz Eleduvith Nu ez Ruiz –
Se ha presentado buena informacion y el profesor presenta un buen dominio del tema.
Gang Ferdinand Dinga –
Good practical analogy and explanations
Pedro Fumero –
Great course. Good basis to CNN.
John Stilwell –
Good delivery, Like the pace, Like the background and personal detail.
Andre Luiz Marasca –
N o consigo entender o que o instrutor fala, ele n o edita os erros de pronuncia e eu me perco no que ele fala. muito dif cil acompanhar uma linha de racioc nio desse jeito…
Christian Valdivieso –
Very good course and very well explained
Hamed Mozaffari –
This course is junk. First of all, the advertisement is a native speaker talking, then the instructor is not a native English. Therefore, hard to understand his voice. Technically, this course is a superficial explanation of basic things. For example, the instructor talks a lot about YOLO, we will discuss that later. And in the section on YOLO, you just learn about the basics of YOLO. Really sad that I cannot refund due to passing 30 days. I absolutely recommend selecting other machine learning courses. Low level Machine learning course with useless explanations of basics.
Salahuddin –
The course is amazing. I am interested in machine learning and that is why is peeks my interest, and so I would recommend it to all those who are interested in Data Science, ML, DL, and AI
Muhammad Ali Bhatti –
a good video
Tauseef –
First of all I would like to thank you for giving life to this course. This course was beyond my expectations regarding Deep Learning and CNN. The course was very comprehensive and easy to understand. The instructors made sure that they are giving the information in a way that won’t make me confused. Thank you so much for this great course! I am glad that I am taking all of your courses to nourish my future!
Abdullah Shahid –
Yes, definately. Got to learn so much from this course. Will look forward for more courses like this in future!
Fernando Zorrilla –
This is a very good start introduction to CNN. It has a lot of concepts and it introduces the fundamental blocks to understand neural networks. If you are strong in mathematics this will be easy for you (it contains derivatives, linear regresssions, Gaussian curves, etc. etc.) I would recommend improving the course with examples , labs or some exercises to put in practice the concepts. For example, for gradient descent concept, please put a running example! Just plot a graphic, and show how we can get the local minimum. It is hard to grasp 10 or 15 new concepts without a single example, just theory. With all the tools and possibilities available, a course of neural networks with ONLY mathematical concepts , it is hard and nonsense. The teacher clearly knows what it is talking about. The course has the hardest part done, it needs to be more friendly. I recently finished another course of Computer Vision from the same author, and that course had waaaaay more examples and labs that this one.
ukasz Bromberek –
The lecturer has an extensive knowledge, and he explains the topic in clear way. The visuals in this course are rather rough and if they would be better I think it would help understand the concept behind theory.
Aytekin rumibeyo lu –
Yeni bilgiler reniyorum.