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Opiniones y comentarios de aprendices correspondientes a Convolutional Neural Networks in TensorFlow por parte de deeplearning.ai

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805 reseña

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If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 2 of the deeplearning.ai TensorFlow Specialization, you will learn advanced techniques to improve the computer vision model you built in Course 1. You will explore how to work with real-world images in different shapes and sizes, visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including augmentation and dropout. Finally, Course 2 will introduce you to transfer learning and how learned features can be extracted from models. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

Principales reseñas

RB

Mar 15, 2020

Nice experience taking this course. Precise and to the point introduction of topics and a really nice head start into practical aspects of Computer Vision and using the amazing tensorflow framework..

JM

Sep 12, 2019

great introductory stuff, great way to keep in touch with tensorflow's new tools, and the instructor is absolutely phenomenal. love the enthusiasm and the interactions with andrew are a joy to watch.

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51 - 75 de 798 revisiones para Convolutional Neural Networks in TensorFlow

por Juan-Pablo P

Feb 20, 2020

This was a great course to go more in depth about the use and implementation of convolutional neural networks. Learn the concept and implementation of "transfer learning" or "inception" to take advantage of CNN trained over a much larger dataset and fine tune the DNN to specialize on a different (but smaller) problem. It was great the learn that one can drop out some neurons from the pre-trained CNN in order to avoid overfitting and specialization. Changing from binary classification problems to multi-class problem is very easy to implement in Tensor Flow / Keras.

por Muhammad U

Apr 14, 2020

Excellent course for a beginner like me. It definitely helped me gaining the concepts and insights of transfer learning and the multiclass classifiers. I am confident now in dealing with the convolution neural networks, coding them from the scratch and to achieve the desired accuracy. The concept of dropout layers has been conveyed in the best possible manner and its affect on the validation accuracy can be easily observed. I would like to appreciate the efforts of the team of Coursera and the instructors for laying down an extraordinary online lecture series.

por Scott C

Jul 10, 2019

Great for people who want to not delve too deep into theory and learn the latest tools to get going quickly. I had already done the Deep Learning specialization so I recommend that as a great complement for the theory part. I learned everything I needed to get going with a practical application in this course. My only complaint is that I felt that the quizzes were poorly designed - most questions emphasized whether you remembered a specific API's argument name, or some questions were a bit ambiguous. Otherwise, highly highly recommend the course.

por Ben R

Dec 28, 2019

This was just an exceptionally well-done course. It's not complicated, but I don't think the point of it is to be complicated, just practical. All in all, I enjoy the teacher's style. If you're trying to understand the fundamentals of the theory and mathematics, these courses aren't for you; if you're looking to just gain a practical and useful working knowledge, then this is a great starting place. I took it to just round out my understanding of Tensorflow via Keras; this was a great course for that.

por Hannan S

Oct 28, 2019

First of all, the course was amazing! I found it great for the following reasons:

- Laurence Moroney (Instructor) was very professional and clear while delivering the knowledge

- The introductions by Andrew NG were really nice

- Easy to understand codes and understanding of thr underlying principles

- Varied topics such as CNN, NLP & Time Series

- Very insightful by providing expert opinions about different ways of model optimization

I really enjoyed the course and I thank the instructor for the same :)

por Victor H

Oct 31, 2019

I am already familiar with machine learing and convolutional neural networks, and before starting using the TensorFlow framework I wanted to develop my own know-how in order to really have control and knowledge on what am I doing. Now that my C++/CUDA implementations work, I feel allowed to use a better tool like TensorFlow / Keras, and I am really discovering their power and flexibility, and I am getting really excited of the productivity that I can gain in my projects thanks to them!

por neil h

Jul 30, 2019

Laurence Moroney presents another superb primer on the mechanics of tensor flow. Heavy on image analysis, we see how convolutional nets — concatenating stages of convolutional filters and pooling — extract features from images at whatever scale they appear. The exercises contain a modicum of basic-python skills reinforcement. Upon completion, one is equipped to tackle other common problems, e.g., the usps handwritten-digits challenge https://www.kaggle.com/bistaumanga/usps-dataset.

por Mastaneh T A

Jun 03, 2019

The pace of these two courses and the extremely to-the-point nature of the explanations, examples, and exercises enabled me to implement customized CNN-based codes my own data in only 5 weeks. Now I am definitely more confident to explore and implement more complex models and concepts in Tensorflow. Thanks to Andrew, Laurence, and the rest of the team for the very efficient learning experience and for sharing their knowledge and expertise.

por Rudraksh J

Apr 04, 2020

Great course, great content, and the best part is you are getting quiz and those "Challenging, interesting, excellently" designed assignments which surely test and improve your real skills. I'm just excited about those assignments every time I progress with a week.

Till now I have completed the first two courses of this Specialization and I'm sure the rest would also be great. I would be taking them all!

por gjycoursera

Jul 01, 2020

greate introduction to Image Classification. The skills is very very useful!

I like this course.

My advise to other learners is reading keras official developer guide(https://keras.io/guides/) when you learn this course. That will be very useful.

Besides, I want to get more skills about Image Segmentaton, Object Detection ,etc. So I hope Deeplearning,ai launch more advanced Computer Vision courses.

por Rishiganesh V

Jul 20, 2019

It is really an amazing course, My heartfelt thanks to Mr.Laurence Moroney, for his great teaching and Mr. Andrew Ng for giving these great platform. I Really enjoyed the course. I learned it lot of things here. I am going to take all the specialization in these courses. And It is great pleasure to thank Coursera platform for providing me Financial aid to take up these course.

Thanks

Rishiganesh.V

por Ali A A

Jun 22, 2020

Great course, well structured and straight to the point, the point being application. Can't recommend it enough for those who completed the deeplearning.ai specialization.

With no sufficient theoretical knowledge and simple python programming, however, the course is vague and highly not recommended. Sufficient understating of how DNN work greatly improves the added value of this course.

por Sachin G W

Jul 09, 2020

Simply amazing! This course felt so engaging and easy. And it had concepts that were taught so well that it felt easy. The concepts learnt in this course are a foundation for building a career in Machine Learning. I learnt about using Conv Nets, Image Augmentation, Dropouts, Transfer Learning, Multiclass classification. Thanks to Laurence Moroney for this wonderfully built course!

por Sreejith S

Jun 03, 2020

Very brilliant course. Lectures are short and crisp, coding assignments are excellent to get you started with dealing real world use cases. Since this course deals with implementation in Tensorflow, i would say, do the Deep learning specialization offered by Deeplearning.ai first and then do this course to glue both the theory and practical implementation together.

por Khanh N

Feb 20, 2020

This course gives me an overview in CNN applying into various fascinating Computer Vision problems, which really excite me. The inspiration that I got would definitely push me to working harder in order to have a successful career as a ML engineer. Also, the teaching style of Laurence is one of the highlight for the course as I found it both fun and effective.

por Edgar C O

Jul 20, 2020

As a follow up of the course "Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning" and as an introduction of the convolutional neural networks for the case of image classification, again, the course is great. The content and the exercises in this course are more challenging and more entertaining to design/program.

por Himansh M

Dec 10, 2019

This course is a great addition to the deep learning courses by Prof. Andrew Ng. I got to learn the fundamentals of deep learning from Andrew Ng's courses and learned to programme from here. It's a great course to learn Tensorflow and this course also helped me in my final year project. I'm really thankful to Coursera and deeplearning.ai for this course

por Sakshi A

Mar 05, 2020

I have certainly enjoyed taking this course. The instructor has been so good at keeping us interested in the course. It didn't really felt like learning. I have learned so many awesome things in this course to help me with the current job as well as inspired me to do some fun work on the photos I have taken myself. Thank you for this course. :-)

por Eulier A G M

Jul 17, 2019

The course is marvelous explain and with clear, concise & straight forward concepts alike the practice project.

Take your time to understand the concepts, so you can move on.

I'll recommend to watch the specialization of Neural Network from Andrew Ng, to deeply understand the "magic" ( linear regression, matrices, derivatives) of Neural Networks.

por Wei X

Sep 25, 2019

I originally expected to learn more pure TF related stuff. But instead I learned Keras. Data augmentation with Keras is quite easy. Transfer learning is also easy to do if there is Keras model there already. But I do hope to learn a pure TF tutorial that are more common when you download other people's TF model and practice with your own data.

por Victor A N P

Aug 25, 2020

Very good course and a good sequel to the first course. These courses give what we need to try our own projects. The course doesn't teach much theory, but it makes us interested and make us search and try to learn on our owns. The notebooks provided in this course, however, aren't as good as the notebooks provided in the first course.

por Pablo S

Jun 13, 2020

Muy instructivo y activo. A uno como estudiante lo obliga a interiorizarse de verdad en los conceptos para comprender mejor las etapas que se deben implementar para el tratamiento e implementacion de una red neuronal convolucional. En general, con explicaciones claras y comprensibles puedo decir que este este un curso muy bueno.

por Anil K S

Jun 12, 2019

This was the actual dealing with the dataset saved at local memory location rather than predefine dataset where the dealing with label and directory were ignored which learner actually face problems while learning and handling with the datasets stored at local drive. well this course actually helped for my major year project .

por Sagar P

Aug 24, 2020

Precise and to the mark. Good brief up of the concepts. 5 stars for ease of implementation through programming assignments. Suggestion to fellow learners: Couple these courses with those by Andrew Ng, so it would be the best merger of theory + implementation. Laurence Moroney never fails individual's expectations. :)

por Ara B

Aug 19, 2019

Easy to follow. a lot of examples. I was expecting at least one assignment for the final! :)

As for the convolution we never talked about DOG+SIFT or other feature extraction techniques. Also I would like to see how we can separate an object of interest from background e.g. using clustering or a video stream.