Traditional neural networks rely on shallow nets, composed of one input, one hidden layer and one output layer. Deep–learning networks are distinguished from these ordinary neural networks having more hidden layers, or so–called more depth. These kind of nets are capable of discovering hidden structures withinunlabeled and unstructured data (i.e. images, sound, and text), which consitutes the vast majority of data in the world. TensorFlow is one of the best libraries to implement deep learning. TensorFlow is a software library for numerical computation of mathematical expressional, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning. In this TensorFlow course, you will learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will learn how to apply TensorFlow for …
Instructor Details
Courses : 3
Specification: Deep Learning with Tensorflow

33 reviews for Deep Learning with Tensorflow
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Price  Free 

Provider  
Duration  15 hours 
Year  2020 
Level  Intermediate 
Language  English 
Certificate  Yes 
Quizzes  No 
FREE
Anonymous –
The instructor seems very active on the forums and even set up a slack for the course. It’s been great, and the homework and notebooks are really easy to follow. So far it has really made me think and seems a lot more engaging than the Udacity or Coursera course. Can’t wait to see where it goes!
Anonymous –
Fun and insightful combination of learning TensorFlow with example applications using neural networks for image analysis, visualisation plus generating text and music.
The course presents a minimal amount of theory, and has a hands on approach. A typical session involves building and running a basic deep network for a task using TensorFlow commands (in Python on Jupyter notebook), getting a feel for what that does, then a guided use of a more advanced model. Assignments start with a 90% complete notebook, with gaps to fill and parameters to adjust.
Sergio Marchesini –
I think this course is excellent and inspiring. The teaching material is very good and the quality of the lessons is high. Just one note: it’s not easy, if you are new to Machine Learning it will take a lot of time and CPU. But it will be worth it!
Anonymous –
Fantastic course, moves very fast, huge learning curve, non programmers might struggle, be prepared for a lot of reading, the instructor is 1 on 1 with every student in the forums, when you finish you will realize you have entered a new universe of possibilities.
Anonymous –
I learned so much! It’s a fascinating course and I’d recommend it to anyone curious about AI or what is possible with it. It’s not an easy course especially towards the end but gives you plenty to think about.
Christopher Kelly –
I have an undergraduate degree in computer science that didn’t include any machine learning and I’m very new to most of the concepts presented in this course. I’ve spent a ton of time on the Khan Academy and Coursera and I’m blown away by the quality and professionalism of the content of this course. Highly recommended!
Anonymous –
This course is really great to learn TensorFlow and manipulate advanced net architectures, like VAE/GAN. The explanations of Parag are great. The code provided for the assignments is just outstanding and is definitively valuable after the course. I need to point out that the community around the course is really active. I had the opportunity to discuss with real creative people, which I have highly appreciated.
Anonymous –
I started taking this course and the most amazing part is being able to see the student work in the gallery. I can’t believe that machine learning can result in images like this! I hope I am smart enough to be able to accomplish this myself. I also see that there is now a Part II and Part III of this course! Lots to learn.
Anonymous –
This is a very hard course! But this is also a very hard subject matter. It is amazing to see this course geared towards Creative applications. Very well produced course. Probably one of the best I have seen online
Kouassi Konan Jean–claude –
As I had already earned the certificate, I think this course is a great one. We have here all necessary tools to understand, master and go deeper in the domain of Deep Learning with Tensorflow.
Anonymous –
Very high quality materials and video. with interesting subject matter. I was looking more for a course introducing working with TensorFlow. I have a deep CS background but limited ML exposure/experience. The sessions started out with a very good balance between hands on development, explanation, and theory, but I felt the Tensor flow aspect of the explanation facet started going down the further into the sessions you got. Too many instances for: “here is some code to run but I don’t have time to explain it”. I really think you should have spent some time on TensorBoard if a good portion of the code you were walking through in Session 5 was there to integrate with it.
Anonymous –
So far, it is clearly the best tensorflow course I have seen. The instructor is very competent, the course material is well designed and extensive, the quality of the videos and the english pronounciation is perfect.
Anonymous –
This course covers what I was exactly looking for. I use it as a reference and keep coming back to understand certain definitions and algorithms better.
Jose Paixao –
Excellent course for anyone without a technical background interested in harnessing the power of Machine Learning for their creative projects. The material is very well organised building up on practical examples and comes with great support from Parag. It has been immensely helpful for my own work and I highly recommend it!
Varun Raj –
Best course to learn tensor flow. You need have a good understanding of NN theory before starting this class. Otherwise you will feel lost very soon. Do Andrew NG’s Machine Learning till week 5 and get to this course to get a good grasp of material.
Overall, great course !!
Anonymous –
Excellent content. The course is very neatly designed and has been presented in an appropriate manner. The course gradually moves from the core foundations to the applications of tensorflow. Parag has done an excellent job in putting forth all advanced concepts. Highly Recommended !
Prateek Katageri
Jay Shankar –
The course is well structured and is good for tensorflow starters. The instructor is very knowledgeable, clear and detailed in his explanation of deep learning & tensorflow concepts.
Pixlars –
Very nice course. It helped me learn tersorflow. It’s a very good course for beginners like me. All the codes very simple to understand.
Anonymous –
Very technical, very informative, really good analysis of the deep learning approaches. The excercises after each lecture are very useful for gathering some hands on experience. Can’t recommend enough 🙂
Mathieu Chauvet –
This course is great, starts with the basics (the one that are not in the Tensorflow documentation!) and progressively goes deeper into tensorflow.
Anonymous –
Awesome course, and the assignments and codebase are a great way to dip your toes into Deep Learning in a creative way!
Anonymous –
I’m a webdeveloper with a good 15 years of experience, but unfortunately I didn’t have a proper education in IT or computer science, although having a general interest in software development. That means, I know my way around producing proper code, but have a harder time following if Math, Statistics, CV and other subjects pop up (as they do here).
The title implies a focus on creative applications, which is a bit of an overstatement. I was expecting some Processing/openFrameworks kind of course. Instead the course goes with a quick pace through all the fundamentals of AI to give the student an understanding on how an AI can draw, produce text on its own or how Deep Dream works.
That made the course that much harder for me, since I lack the basics, and I struggled a bit with the exercises.
I still give the course five starts, because the video material and explanation is really well made, good to follow and I got a lot of insights. There is tons of material to work on and the Jupyter notebook are well made. I actually spun up an easy network with Keras after the course and was super excited to understand all the terms and how AI networks work at all.
I don’t think, I could have had a better intro to AI. Thanks Parag Mital 🙂
Gabriel Montagne –
This is a great course the approach is quite unique compared to other Deep Learning courses as it is geared, from the outset, to doing creative work: visualisations, image processing, and generation.
Funnily, this actually helps to understand the core underlying concepts even better than if it was just a “formal” course on Deep Learning as one actually sees and gets a deeper intuition of how training hones (or diverges, when things go wrong) over solutions, how different activation functions “look”, and, doing generation, how the models “understand” what a face is, or what a word (or the sound of the word) is.
Parag, the teacher, is clearly very fluent on the material and can reconstruct, from the ground up, the fun things going on in the DL world, as opposed to just hooking into some “style transfer library somewhere”.
One wishes, though, that he had more assistants to help update all the examples and tutorials and libraries he provides as the underlying libraries like TensorFlow evolve and break their old APIs.
One last thing, for me very important: the course is running in “Adaptive Mode”, which means that one can truly take time to master each of the chapters before moving forward to the next concepts. This is a truly great thing that separates this course from others which might also have great content but for which you have to cram up the material just stay on board.
Rates –
This course has decent content, but the pedagogy is pretty unpolished in my opinion. Parag doesn’t spend enough time convincing the student WHY they should care about what they are doing or provide enough context of where this material is situated in the wider landscape of machine learning, art or design. He gets straight into the technical details of the tensor flow library without really explaining where the student is going. As a result I spent much of the time wondering what the point of each exercise was. Why does figuring out the (trivial) syntax for a snippet of python code from a 3rd party library help my art practice, or my understanding of machine learning? The net result is course material that is neither conceptual and high level or low level and technical, but a grey blob somewhere in the middle.
Kuram Sreevallabhan –
overall the class explanation is good. but i think classes should cover few topics into deeper because most of the learners are new to the course
Rahmanuddin –
This is the course I was looking forward to enrol in to. DNN Implementation in various environments. Very supportive forum plus detailed instructions and on screen examples. Hard to resist to start next session, but I must say, I am taking one step at a time and first practising whats being taught and then moving onto to next session. Though you might be missing a smile on the face of such nice tutor, but never the less lost of love and respect.
Zubrycki Igor –
The course was very good and inspiring. It is obviously not for everyone as the focus in on the artistic use of deep learning, however, this type of application is fun and quite easy to experiment and learn in the process.
Joshua Newnham –
Great concept and a really interesting application of AI useful course to help fast track you into using AI for creative purposes. It provides inspirational projects that are beyond ‘toy examples’ and you are encouraged to explore and experiment to learn and better understand how they work. Recommend for anyone who has experience with Deep Learning and wants to delve into the world of Creative AI.
Anonymous –
Very useful especially for those new to tensorflow and python! Layers are built manually which provides a good understanding on how Deep Learning works.
Highly recommended and a very professional course
Anonymous –
After taking several courses in Machine Learning, I came across ‘Creative Applications of Deep Learning with TensorFlow’ from a github link. After the first preview video, it immediately caught my attention due to the the speed of delivery, content topics and it’s pace when talking about concepts such as gradient descent and convolutions. Honestly, the course truly is EXCELLENT. Parag really is great a presenting the materials in an easy to understand manner, and perhaps more importantly, he has you focus on the RIGHT concepts and not going down rabbit holes.
Anonymous –
Just completed this course, but decided to stick to free tier and not submit assignments.
I was looking for a course to get started with TensorFlow, and this one is ranked as the best one. The course is great and fun, but I don’t feel that I’ve got comfortable with neither machine learning concepts described in the course, nor with TensorFlow.
On the other hand this is not a TensorFlow crash course, it is specifically what is stated in title creative applications for deep learning. I don’t regret the time I spent taking this course, it was fun and I learned a bit about advanced state of the art techniques in deep learning.
Sakthi Priya –
This is a great course the approach is quite unique compared to other Deep Learning courses as it is geared, from the outset, to doing creative work: visualisations, image processing, and generation.
Anon Yme –
Damn! This course is the real thing. You will learn how to use Jupyter notebooks, python, tensorflow and actually make some dope images. There’s a lot of state of the art in this. Would highly recomend as he gives you the basis for which you can explore your own creative projects.