i have completed course1 and course 2. i want to learn deep learning . what is the next step from this course. i know there is a DLS course by andrew sir. but it was launched 5 yrs ago. i have also done the old MLS course. these 2 have lot of difference in terms of techinques used,etc. i want to whether DLS is compatible with new MLS.(for ex does it use keras or latest techniques ).i liked the new MLS course,it’s much better than old one. can the dls course be considered as an extension of this course or is it slighly dated(mainly in terms of coding,i assueme the concepts r still very relavant)?. i just want to learn the latest deep learning techniques,like i did in this new MLS course.will there be a new DLS course or is there any other new/recent Deep learning course with latest techniques or atleasat a guide.I guess the concepts from DLS are still relevant and useful,but im also worried about code. like i have learned keras here and to use something entirely different seems redundant.I apologize if i am coming across as rude. i just want guidance. which DL course be a perfect extension of the current ML course(atleast code wise,like i can learn concepts from DLS and coding from some other course or source,is it even possible?if yes,suggest me).thankyou in advance.
The Deep Learning Specialization is the next logical step after you’ve completed either the original ML course, or the new ML Specialization.
is it compatible in terms of coding techniques too? (keras etc) also where can i find some good practice projects for neurals networks. i want to practice more of what i have learnt in course 2.thankyou
The Deep Learning Specialization uses TensorFlow (including Keras), and has many programming exercises.
For practice projects, there are many datasets available online for free that you can download and experiment with. The “UCI Machine Learning Repository” is one.
Or you can join an online machine learning community, such as Kaggle. They have many tutorial projects you can access.
Hi @TMosh ,
In terms of courses, what would be the entire Machine Learning Engineer path that you recommend?
Sorry, I’m not able to give career advice.