The specialization covers brief introduction to the concepts of Computer Vision and Natural Language Processing. It introduces to TensorFlow and gives a hands-on practical experience over the tool through simple assignments.

Learnt a lot of new things about image classification, how to better predict images using TensorFlow. Laurence Moroney is a great teacher who skillfully explains the code and its significance in an easy-to-understand manner.

Incredible course structure. Really well designed and thoughtful. The programming assignments were especially very helpful. Grateful to Coursera for letting me do this specialization during these uncertain times of COVID-19.

It's a nice approach and a good example of how we're going to do Machine Learning stuffs through an open-source library called Keras from Tensorflow (from Google ofc). Thanks, Google and DeepLearning.AI., Mr. Andrew Ng!

The instructors explain very good, the team is polite and help to answered my questions. The material is very clear to understand, and we have hands on to practice the knowledge from the lessons. I enjoyed very much.

Very instructive and practical, but the coding assignment can be mis-leading from time to time. However, that is not anything out of ordinary, practitioners should expect some level of sophistications in real life

Coming from an aspiring Data Scientist, Laurence Moroney provided succinct explanation on practical aspect for CNN, which is a definitely a supplementing course material alongside Deeplearning.ai's specialisation.

very well explained and the google colab notebook that they share is very helpful . i recommend to go through the lectures and go through youtube videos for deeper understanding before just jumping to exercises.

Just a few weeks ago I was hoping for the day I learnt to properly feed a neural network with a real dataset of images. I didn't expect to find such a good answer in this course but I did. It does exactly that.

This specialization is really helpful. I had done other specializations and Machine Learning Course of Andrew Ng. But this course helped me to revise those topics as well as implement them in the real world.

After finishing this course, I was able to build a neural network that could identify different types of boats with around 94% accuracy. I used many techniques learned in this course like image augmentation.

This is a very good course to start on TensorFlow. It requires certain amount of knowledge ( I recommend Deep Learning Specialization). I started kaggling after this course and the results are very decent.

IT is a great course about Deep Learning and above all, how to code it with Python.

It is very practical and you learn a lot of features about the Tensor Flow framework that you can reuse for other issues.

Really enjoyed the course. Thanks deeplearning.ai team. Except "Inception" every topic was clearly practiced. For "Inception", I am eager to learn how to lock a model & how he trained weight can be saved.

A really good course that builds up the knowledge over the concepts covered in Course 1. All the ideas are applicable in real world scenario and this is what makes the course that much more valuable!

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..

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.

Excellent and detailed on how to create a convolutional neural network using TensorFlow as well as explaining how to solve problems such as low accuracy, overfitting and even improving the dataset.

If you are looking for a course to build up your ML/DL coding skills, this is a very interesting and easily explained course. Highly recommended for any learner in the field of DL/Computer Vision.

Nice course, my knowledge in machine learning increase after learn in this course. i have some experience in model overfitting, binary classification, and multi-class classification data image.

Laurence Moroney is the best. Before taking up the course, i didnt know anything about the AI or ML or Tensorflow. The concepts were explained in such a manner that anyone can learn Tensorflow.

For the 4th Week, It might be useful to explain the difference between categorical and sparse_categorical crossentropy for multiclassfication case and what does the term 'hot-encoding' mean

a very nice course on ConvNets. Image journey through convnets and logic behind using specific type of layers. you can very wellunderstand the keras structure to build convnets through this.

Loved it. It was surely targeted for beginners first two weeks assignments were easy last two assignments had some work to do. But most of the Hints/answers are available in the comments.

I gained a hand full of knowledge from this course.

This course has given me a very good insight into convolution neural network work.

I thank Laurence Moroney and Andrew Ng for this course.