糖心vlog官网观看

If you're starting out as a beginner AI practitioner, this is a very good introductory course. The prerequisites for going through the classes are really low. You just have to know basic python and the basic mechanics of deep neural networks beforehand. After completing this course, you'll be very proficient at modelling neural networks to classify images with very high accuracy using tensorflow keras.

This course also explains briefly how to import data of your choice to your neural network to train on, which I think is very cool. It also teaches you about convolutional neural networks, which is what the top industry experts use to do their AI jobs. The exercises in this course are well made, they help you really understand the concepts by making you code them by yourself. All in all, this is a very good introductory course, and Andy Morone is an amazing teacher.

This course is very friendly to beginners starting to get to know TensorFlow. The only skill needed is basic Python programming. Another good point for this course is students don't have to obtain a local machine that could run the TensorFlow. The tasks could be done over Google Co-lab, which is very conveniently friendly. The only shortcut for this course would be the source codes provided are based on TensorFlow 1.X. Right now, the TensorFlow has released 2.X. Since tf V2 has taken out some functions in V1 as well as changes some expression, it would be very inconvenient if you wanna download the code and test or do your work on your local machine.

Overall, this is a course that I would highly recommend as a beginner.

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning by deeplearning.ai on 糖心vlog官网观看 is an outstanding course for anyone starting their AI journey. The course introduces complex concepts in a digestible manner, making the learning curve manageable. The blend of theoretical and practical knowledge is balanced, thus providing a comprehensive understanding of the subject matter. The assignments, while challenging, are designed to reinforce learning and encourage practical application of concepts. They push you to think critically and problem-solve, rather than just follow instructions. Although complex, resources and hints provided make them achievable and fulfilling.

As an introductory course to the Tensorflow platform I think it is excellent. As it is mentioned in the title this is not a course where you are going to see in depth what it is behind the algorithms or the theory behind the implementation but it provides extra links to other sources where the interested student can read on their own, which I think is good. It is self-contained, the material in the course it is well explained and the ideas about how to use the platform and the ideas of how to solve the problems are well-defined. The exercises are defined in such way that the student can immediately used what he/she learned from previous materials. It is a great introduction to Tensorflow.

The Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning course offers a concise yet comprehensive overview of TensorFlow. This course provides valuable insights into the core concepts and practical applications of TensorFlow in the domains of artificial intelligence, machine learning, and deep learning. The content is presented in a concise manner, allowing learners to quickly grasp the fundamentals and apply TensorFlow effectively in their projects. With a strong emphasis on hands-on exercises, this course offers a practical learning experience that enhances understanding and builds confidence in working with TensorFlow for AI, ML, and DL.

This is an excellent foundational course on a complex topic. I especially like the application of the course examples in real-world deployment type assignments. The use of colab is very nice, it is not a technology that I have used before however its 'jupyter' like interface is very comfortable and I like how it is deployed and accessible on virtual machines all the time. The only criticism I have is that the assignment grading is a little rigid and there is not a lot of valuable feedback if fails (i.e. it could be badly coded or it could be something as trivial as using the wrong number of nodes in a layer! - this could be explained better I feel)

Amazing class! As an absolute beginner, I wanted to learn machine learning and AI but didn't even known where to start. I even started a different machine learning course which I could not follow well, and expected similar results with this class. But this class, this class is aimed at beginners, no need for any pre-requisite knowledge and the google colab environment ensures that it doesn't matter what hardware you currently have, since its all done in the cloud. Also the practice notebooks are very detailed about each sections of the program. I'm not a master at machine learning, but atleast after this course I feel that I too can learn it.

I have used Tensorflow in my projects but never know some of the tricks which could improve the model.I was very dependent on transfer learning. But, now after getting to know much about Tensorflow, I feel so confident . A basic understanding of how model works with Tensorflow is essential and Laurence Monorey provides you some of those basic tricks and concepts of how neural networks works with Tensorflow. I can assure anyone here taking this course would definitely give a try to adjust the way they have approached towards implementing Tensorflow in their projects. Thanks Andrew and 糖心vlog官网观看 for bring up this initiative.

The first MOOC that I completed! Firstly, thank you so much 糖心vlog官网观看 for the financial aid and the flexible deadlines! The course is really easy to follow. Awesome videos and notebooks provided. Instructor can really convey the material to learners. Best paired with additional research about loss functions, optimizers, activation functions, and TF/Keras layers. Prior knowledge with Andrew Ng's Machine Learning Course (the Matlab/Octave one without Tensorflow) is also helpful as it gives a good intuition on loss functions, gradient descent, activation functions, and neural networks. Well done 馃憦馃憦馃憦馃帀馃帀!!

I found this course very helpful because of working example at every step. First there is step by step explanation of each line of code after which you can play around with the code by making small modifications to it and observing results. It is not heavy on math behind machine learning but there are certainly lot of new terms. Most of time i googled those term to learn a bit more about those. Overall, instructor explanation is extremely good and easy to follow up. Its extremely important to play around with the code samples. All i needed was a browser and no installation on my laptop to finish this course.

FANTASTIC!

I love the courses put out by deeplearning.ai. I previously took the 5 course deep learning sequence taught by Andrew Ng (which I would also recommend), and am VERY pleased with the first course of this sequence taught by Laurence Moroney.

The lectures are broken into small, digestible chunks. The quizzes are hit core knowledge points w/o any tedious "can you do this by hand" nonsense you see in some other courses. The notebooks provided in the course offer useful templates for adapting to other problems. Just amazingly well done in every aspect.

Looking forward to taking the rest of the sequence!

"Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning" is an excellent resource for beginners who want to learn the fundamentals of TensorFlow. The course covers essential topics such as neural networks, deep learning, and convolutional networks, all using TensorFlow. The writing style is clear and concise, making it easy for readers to follow along. The practical examples and exercises provided are helpful in reinforcing the concepts learned. Overall, this course is an excellent starting point for anyone interested in learning TensorFlow for AI, ML, or DL.

Excellent for any beginner. Watching Andrew Ng anywhere gives you a sense of authority and validates everything. But all the teaching part is done by Lawrence who is equally humble and knowledgeable.

All the theoretical topics covered are explained in brief but there are ample resources on the internet to understand them thoroughly.

The coding part is very easy to follow.Although some python code blocks were typical to understand but again you can always look them up on the internet.

Overall it is a brilliant course for anyone who wants to start with Keras, tensorflow, deep learning.

I quickly fell in love with the approaches used by the tutors to introduce new concepts through simplified videos, allowing me to explore them on my own in the Collaboratory Notebook. In addition to that, the questions used in the quizzes were pretty accurate, and going back to them later helped me clarify some misconceptions and learn from my mistakes. The assignment papers at the end of each week also allowed me to review what I had previously learned and question my acquaintances. It's been overall a wonderful experience and I am looking forward to extending it even more.

This course is an excellent starter for people who want to learn about Tensorflow and how to use it to create neural network model very quickly . The Instructor explains every thing in very lucid language.Course is well organized to help you go from beginner to an intermediate quickly. Great articles and videos links will also come your way so even that would help you improve and enhance your knowledge. Highly recommended for someone who wants to learn about Tensorflow and enter into the field of ML & AI. A Big Thanks to deeplearning.ai for creating such course :)

I love the following things about the course:

a. Very calm, consolidated, and well thought of introduction to TensorFlow. The documentation could be a little intimidating for a newcomer. But this course is a step by step guide.

b. The exercises encourage you to explore more. When you explore more, you learn more.

c. The workload is just enough and you can manage it with your regular course studies and student jobs.

What I wish I had a little more from this course:

a. I wish there was some element of NLP in this course. A little would have helped.

Great learning experience overall... Prof. Moroney was very patient in his approach and took his teaching one step at a time. So I never felt like I was taking too huge a leap at any particular one time. The links he provides for study were also helpful.

It was obviously a plus to have a great teacher like Andrew NG chip in occasionally a word or two.

Overall, it's a great course and I'd absolutely recommend to anyone interested in exploring the possibilities that computers of today give us in exploring our world.

The course material and presentation is excellent. However some of the course tools are complete trash (code autograder in particular - this is because the code that was shipped off to the code autograder wasn't the code I had been working on - it wasn't until later that I realized that the tools were taking predefined [expected] file names and not the code I was working on - this is only year 8 of this otherwise excellent project - 8 years and the tools are still substandard). Also the quizzes are too easy.

When I joined this course, I did some basic projects with tensorflow. But they way Mr.Laurence Moroney took me going through every details of codes,and sharing the ideas and concepts why we use this, when we use that etc., I was so encouraged that I've spent hours to tune the parameters etc. Hats off to deeplearning.ai that I'm able to learn from the experts. At last but not the least, Prof.Andrew Ng has always been an inspiration to me and I'm grateful that he motivates me always by teaching AI like stories.

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Great course! Thank you for the opportunity to pass. Very informative explanations. The videos are short but very full. All links to more in-depth information have been provided, and all sources and hints have been provided. A very good approach to student learning

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 :)

糖心vlog官网观看 and of course the instructors have really got this online teaching down to a science allowing students to cover often quite complex topics in an easy to digest and efficient manner. Even though it does skim the surface it does give a very good 10,000 foot view of the objectives and capabilities of the topic and technologies. To get same perspective on my own would be a lot of googling, trial and error, without the benefit of knowing 100% that I was covering the appropriate knowledge.

Introductory level course. Perhaps the best feature of this course is that you start to learn by doing right from week-1. The instructor doesn't spend time explaining every line one by one with every detail. That leaves you to figure out a few things on your own due to which you're bound to remember these details. Notebooks are also much better than the deep learning specilaisation. I often found myself going through the tensorflow documentation - learning and exploring as I did. Fun course!

Cours int茅ressant, clair et facile 脿 comprendre. L'enseignant est tr猫s sympathique et semble passionn茅. C'est 茅galement facile 脿 comprendre m锚me pour un non english native speaker.

J'ai d茅j脿 suivit les cours d'Andrew Ng et comme de nombreuses interview d'Andrew et des r茅f茅rences sont donn茅es dans ce cours cela les rends tr猫s compl茅mentaire.

On a qu'une envie c'est de continuer pour en prendre plus sur ce sujet passionnant.

Je suis tr猫s satisfait de suivre cette sp茅cialisation

Gilles Pierre

Perfect Course, It tells you how to implement basic neural network to deep cnn.

Week 1 : Intro to tensorflow/keras

Week 2: building dense neural network; 2 applications fashion mnist and digit mnist

week 3: building cnn, improving accuracy on week 2 applications

week 4: using image generator to auto label the images, horse/human classifier and happy/sad classifier

Overall a perfect course to begin with, though i would advice to have basic understanding of neural network and its working.