In-Depth Udacity Deep Learning Nanodegree Review

what's going on learners welcome to my deep learning nanodegree review video so in this video I'm gonna break down the what when why where and how of the deep learning no degree or at least share with you my experiences of each of those so I've created my own artificial intelligence master's degree essentially just grabbing courses from the internet and combining them into a a bit of a structured curriculum so I have an idea of what I'm doing and the deep learning nanodegree was a major part of that everything I talk about in this video by the way I'll be linking in the description so if you if you want to find anything it'll be down there as simon Sinek says let's start with why why would you want to do this course well if you want to get into the field of AI deep learning is where it's at and I'm just breaking into the field at the moment I'm still learning but from all the research I've done and that has been my main focus for at least of the past year or so it's a deep learning is is the forefront of AI and as Andrew Allen says AI is the new electricity artificial intelligence in the future or already now actually will eventually break into every industry so if you imagine how electricity changed every industry that's the same thing that's going to happen with artificial intelligence once our machines they're powered by electricity now they're gonna be powered by intelligence and so that's gonna deepen our interaction with them further and further so whatever industry you're in whether finance health anything artificial intelligence will affect you in some way and at the moment deep learning is the forefront of that that artificial intelligence so having an understanding at least an overview of it I think will be very helpful in that a warning history you're in so before you sign up I think it's important to think about why you want to sign up so I'm just going to talk to you about going briefly of why I signed up to the course so in the past I'd done some programming some well it wasn't it really programming it's just like web design web development I did the first section of free code camp if you've ever heard of that before and then after I did more and more research into the world of tech I've always been interested in I graduated in 2015 with the nutrition degree so I've been interested in health but tech is something I finally decided to get into and start actually making things but I found that programming was moving more towards from giving the computer instructions rather than telling it what to do it's moving to showing it what to do that's a quote from Geoff Hinton by the ways programming is transitioning from telling a computer what to do to showing computer what to do and that transitions into into the what actually and we'll get to that in a second about what is deep learning and so I stumbled upon this this course on Coursera I was browsing through the nanodegrees and then I saw Suraj's videos and that really encapsulated me the way he was teaching the way he was so passionate about these things and I heard about artificial intelligence but not in the way that he was talking about and so he really inspired me to sign up to the deep line now who agree and then as I got into it further and further I got a few months in I realized that artificial intelligence is the place I need to go to and that's how I created my AI master's degree and then that's where we are today so we're finished with Y let's move on to what first of all what is deep learning deep learning is just a neural network with more than one layer so if you imagine a lasagne right you got sheets of pasta and say a normal neural network is just a lasagne with only two sheets of pasta not a very fun lasagne but then it becomes deep once you add layers of layers of pasta right you can imagine deep learning as being a lasagne with three or more sheets of pasta and what does this mean what why am I talking about sheets you can imagine the sheets as layers in the neural network if you've never heard of a neural network just imagine a neural network is very simply just being something that you you take an input you do a bunch of calculations aka move the input through different layers and the calculations are a mathematical calculations and then as you move it through the layers it refines that input into an output and then the output is something that you can use that gives you more value than the original input so what are the prerequisites of the deep learning now agree from my perspective I signed up I don't need to have three weeks of Python experience in a high school math education you can probably do it but beware I found it pretty difficult what would the actual prerequisites be if you can if you have any programming experience at all let's say six months to a year in Python Java C++ or something like that or if you have a high school math education or undergraduate math education you be more than ready to take on a deep learning nanodegree however if you don't have those things you can do what I did I up school up skilled myself on places like tree house they did the Python programming track on there and for the math I've learned - all through Khan Academy so linear algebra math sorry matrix multiplication or matrix math bunch of calculus as well the guys at Khan Academy this is a it's a bit of a digression but that's an amazing place to learn anything else that you that you need on my mind and it's completely free don't worry too much about the the programming needs and the math needs you've had a high school math education and you've done a little bit of programming before aka a month of - be more than enough jump into the deep learning nanodegree so what's covered in the deep learning that Avery what's broken down into five main categories first of all is neural networks so building a basic or your first neuron network and it's convolutional neural networks there you classify different dog breeds using actually convolutional neural networks imagine them used for computer vision so anytime you see a facial recognition system or something classifying something as a or your if you have a drone that clusters fires different objects or if you're taking a photo on your camera and it can see faces that's probably a convolutional normal network and then the recurrent neural networks so recurrent neural networks imagine it to do with anything to do with language so Google Translate is powered by recurrent neural networks in the recurrent neural network project you will work on generating a TV script what that means is you'll take a corpus of text and create a brand new TV script what I did is I worked on took 22 seasons of The Simpsons text and created a totally new scene at Moe's bar which was actually really fun for is generative adversarial networks so this is actually relatively new in the field of deep learning so it came out in 2014 by in Goodfellow and it combines game theory and deep learning and puts them together and you create some awesome things in the project and the deep learning a degree you'll work on generating faces with gans or generative adversarial Network so what that means is you'll take a data set of different celebrity faces and use them to generate new faces it's mind-blowing and then the new content which I haven't done yet is deep reinforcement learning so this is number five which is actually really exciting for me I wrote an article on how google's deepmind are using deep reinforcement learning to build smart agents to play Starcraft 2 in the deeply reinforcement learning from what I've read I haven't done it yet you will learn how to teach a quadcopter or a drone how to fly some really exciting stuff in there to work on one of the great things I love about the project is that you dive straight in and start building these deep learning neural networks straight from the start so from the project one which is your first neural network straight in with convolutional neural networks you're building these deep learning architectures that are world class so it's something that would be in in production level people in extract companies and and startups and whatnot these are the same type of networks that they would be using there and that's what I really like you sort of you're diving into the deep end rather than you do build a foundation of knowledge but then you're going off the cliff here you take the training wheels off set yourself on the path of of building a deep Learning Network of your own what that means is that if you like me and you've had a little bit of you haven't had much programming experience you will probably find it a little bit difficult but you can get through it if I can get through it so can you I'm not special at all I just just work through it ask for help and that's another thing you get a dedicated slack channel to the deep learning than a degree which is incredibly helpful there's thousands of people in there so so make sure you if you go in you say hello I'm pretty sure you can join it without actually being a member of the deep learning and agree I'm not entirely sure so don't quote me on that and the forum has plenty of questions trust me if you do you think of a question when you're working through a project or working through a class chances are because there's so many other people that question has been answered so you'll be out of get a valuable answer from the forums or from the slack if you have any trouble at all and that's something I need to learn from the start as I was I was spending too much time trying to do it all myself so don't be afraid to reach out for help another thing with the projects the feedback is in credibly fast I would submit a project and the submission form on the Udacity nanodegree in the classroom sorry says you get feedback within 24 hours and usually it's in within less than that and the reviewer has incredibly detailed feedback on on where you can improve your model you can even directly ask the review up when you submit it specific questions say for example I want to improve section three they will give you some more resources on how you can improve section three so what else do you get from the deep learning nanodegree well you get guaranteed admission into one of Udacity z-- higher level nanodegrees that is the artificial intelligence nano degree self-driving car nano degree or robotics nano degree and right now I'm enrolled in that artificial intelligence no no degree I've just finished term one and I'm starting term two in a couple of weeks which is based on deep learning so it's more it's more projects on deep learning so I'm really excited for that part these probe's these programs aren't as accessible as the other ones you have to do you have to go through an application process to get in because they are they are quite advanced and so the deep learning now that agreed gets you guaranteed admission into one of those of your choice so let's get on to the house section first of all how much does the deep line now eageriy cost well in my country Australia it is 750 Australian dollars so that's 750 dollars for four months or so tuition so it's around two hundred dollars a month and how do you learn how do you learn inside the what is the classroom like you sign in so I can online learning platform it's actually one of the best I've ever seen and you go through you've got your different modules on the left and then as you scroll through you've got all the different classes that are involved with that module how do you do the assignments so the assignments are all done or mostly all done in Jupiter notebooks which are my favorite thing to to code up anything to do with deep learning or Python and so that Jupiter notebooks are incredibly simple to use incredibly easy you can just type in Python straight away and it's all built in you can import different libraries to them there are some steps in that their instructors go through in the d-plan you know Toby reads again your environment setup and if you're not sure what environment means just just imagine as giving the right programs ready to run in the Jupiter note once you've completed an assignment you submit the Jupiter notebook as well as the HTML file and any other files that are associated with it that you need to submit you submit that through the Udacity submit page and then a reviewer will get back to you within 24 hours with all that feedback that I mentioned before and it's it's I can't rave about this enough the reviewers the best reviewers I've ever had on any of my assignments in any of my previous education and I spent five years at university so how much time will it take well quote on the website is 12 hours per week I was doing a bit more I was probably in the range of 15 to 20 and I had the privilege of being able to study study the deep learning an agree almost full-time the reason why it took me so long was because I was unfamiliar with some of the concepts so if you wanted to prepare better for it could go over some Python modules Udacity have great introduction to Python or the intro to machine learning course on Udacity that's another great resource to start and that will probably lessen the amount of time you have to put in per week so if you have limited time I would say make sure you're well and truly prepared by getting on top of your math skills and linear algebra I go through courses on Khan Academy that will put you in the ballpark of 12 hours per week if you like me and you're sort of still new to this stuff you can do it by all means you can do it but just be where you're gonna have to dedicate more time even if you are experienced it may take more time because some of the concepts are quite difficult have a baseline of 12 hours per week and I would probably buffer it up maybe an extra three so between hours per week just to be safe how did I take notes one of the big things people ask me in some of my videos is how do I take notes right so I've got like I always have a paper notebook with me while I'm watching things in the classroom and I'll always have like a I bear no to open like there's a note taking application for Mac or Evernote or something like that next to the the classroom window what I try to do is I watch the videos I mostly watch them on 1.5 speed I just to get through them they are relatively short videos and the deep line you know degree so so you can get through a lot of videos really quickly what I will often do first is if there's a summary video at the end of at the end of a class at the end of a course or something like that or an end of a module what's the summary video first and take it and write down the takeaways from that summary video then I'll go back to the starting video of the of the class of the module and go right back through the start and go through them all then what I will do is if there's sort of questions relating to the videos I'll start to take notes I'll rewatch the video and start to take notes based on what those questions are there's a really fundamental point that comes up in one of the videos I'll pause it write it out by hand about what I think and then go on from there what I try not to do is be taking too many notes while the person is speaking I try to listen while they're speaking and then let that process and delay what I've understood from the video in my own words because otherwise just be literally copying down what they what they would say in summary I go to the summary lecture first get the summary points or the objectives I'll read the objectives and write down the objectives of the class they're the main key points and then I'll watch the videos on 1.5 speed and take away any key points from from each of the videos but I'll try not to be writing too much while the video is actually playing now that's my learning style it may not necessarily work for you give it a try I found it works most effectively for me out of all the learning I've done listen first and then write down anything you take away in your own words where and when these two can be covered pretty easily so where of course you can study online so anywhere you have a laptop or an iOS device the Udacity classroom is available there beware you won't be you do need a web browser to do the projects and some of the questions on the lectures and the classroom you won't be able to do the projects on an iOS device at this stage that I'm aware of I did all my projects on my on my laptop anyway when the course is it starts every I think it's every four months so it takes four months and it starts about a new cohort starts every four months from Alice standing that may be chain that may change in the future as more and more people get interested in it there are due dates for the projects however they are soft due dates so if you miss them by a couple of days I missed them by a couple of days sometimes you will still be able to submit the project and get it marked by a reviewer however there is an end date the course say your starting date is day one you'll have four months from day one to the end to submit all the projects usually there's a project due every month you'll have four months to submit all the projects and if you don't submit them all within that time frame then you you will have to do the program again you'll have to re-enroll and and pay that fees so let's wrap this up what's my overall verdict of it I loved the nanodegree the deep learning a degree is amazing do I think you should sign up for it if you're interested in deep learning and you want to get a great overview and start getting into building deep learning models Udacity is a great place to start there are more and more deep learning resources coming out online such as alternatives you could go to deep learning on Coursera or you go to the fast AI they are both courses that I'm going to do I'm currently doing the the deep learning course on Coursera you can find all this out in my self created AI master's degree article that I wrote up at the Udacity one $750 Australian or $600 us may be quite expensive to some people fast on AI is free Suraj's videos or suraj revolve he is amazing a eye educator his videos are all free Coursera is about 65 Australian per month I'm thinking that's fifty five or fifty US dollars per month so that's a little bit cheaper you can get all the courses done a lot quicker on there of course the deep learning a degree is a $750 upfront fee or $600 u.s. upfront fee they are some alternatives you can try but the deep learning nanodegree I believe gives a great introduction to deep learning when I graduated did I feel comfortable making deep learning models from scratch no but that is because of I I didn't go into it deep enough yet I could take the materials from there and reproduce them and go through them again and again and practice on implementing models of my own like what I did take away from it is I can now understand what people are talking about in the world of deep learning to take it further what I would have to do and what you would have to do from from the deep learning nanodegree is really work on building the models yourself when you work on the projects in the deep learning now a lot of them I would say 50% at least I've done for you so you get the skeleton project of course and then you fill it in with your own code and different algorithms you want to get better at implementing them yourself you could practice on the projects and then delete the code and then rewrite it yourself means when implement it from scratch I'm not up to that stage yet but it is something I'm working towards and another great takeaway from the Udacity deeply nano degree is the access to the guaranteed admission to the higher level nano degrees which I'm currently doing now that's another great reason to to do it you get a incredible overview of what deep learning does you get experience building real world deep learning models and the latest technologies the deep reinforcement learning module just came out I'm excited to do that and you get access to the high level memory so they're the main two takeaways third one you have access to the slack channel which is thousands of other students like you who are interested in technologies that are going to change the world of software of AI of plenty of industries those are the three main takeaways for me and out of 10 rating for the D playing now that agree I give it a 9 out of 10 because it's not perfect there is some improvement no course is perfect so it's it's close to it 9 out of 10 if you want to see more of exactly how I went through the deep learning nanodegree check out my hundred days of code series on YouTube all my hundred days of coast series on medium which is writing if you prefer reading it or otherwise I also have a series of articles called how I'm learning deep learning part one two and three so far part four will come out in the near future of how exactly I'm going through learning deep learning there's some other great resources for you to check out out how I did it and what my impressions of the deep learning nanodegree are as well as how I'm learning the things surrounding deep learning such as the math and the Python programming that's required for it otherwise thank you so much for watching this deep learning that a degree review video I hope you got some value from it and if you have any more questions at all that I haven't answered throughout the video leave a comment below and I'll answer it so that other people can see it or if you want to send me an email my email is daniel at mr deburr comm and I'll do my best to answer any questions that you have subscribe or leave a like if you want to see any more videos like this in the future I'd really appreciate it but it as always keep learning you