1 00:00:01,120 --> 00:00:06,700 Hey, guys, in this lecture, I'm going to show you how to set up your development environment so that 2 00:00:06,700 --> 00:00:08,680 you can follow along in these courses. 3 00:00:10,690 --> 00:00:13,140 First, let's talk about operating systems. 4 00:00:13,900 --> 00:00:16,870 The three big ones are Windows, Linux and Mac. 5 00:00:17,680 --> 00:00:21,400 Most but not all of my courses are part of the Deep Learning series. 6 00:00:21,920 --> 00:00:28,180 Eventually, the deep learning models were going to build will become so complex that we will need specialized 7 00:00:28,180 --> 00:00:31,560 libraries like V.A. intensive flow to implement them. 8 00:00:32,320 --> 00:00:37,450 Now, as of today, Viento intensive flow are not officially supported on windows. 9 00:00:38,380 --> 00:00:43,600 So if you are interested in deep learning, you will discover pretty soon that there is not much you 10 00:00:43,600 --> 00:00:45,130 can do without a ton of work. 11 00:00:46,210 --> 00:00:52,570 Even working with non GPU enabled libraries like numpty and matplotlib can be a challenge, but these 12 00:00:52,570 --> 00:00:54,370 are at least possible on windows. 13 00:00:55,300 --> 00:01:00,550 If you really must use windows and have your python environment inside of windows and you don't want 14 00:01:00,550 --> 00:01:06,070 to try the virtual machine method, which I'm going to discuss next, then one good library I know of 15 00:01:06,070 --> 00:01:07,330 is called Anakonda. 16 00:01:08,470 --> 00:01:13,050 You can get Anakonda at Continuum IO downloads. 17 00:01:14,170 --> 00:01:20,080 I can't vouch for this 100 percent because I haven't used it myself, but I've known others who have 18 00:01:20,080 --> 00:01:21,340 found it at least usable. 19 00:01:22,240 --> 00:01:24,010 Now I'm telling you this from experience. 20 00:01:24,400 --> 00:01:30,070 I've worked with a ton of clients one on one, and python development, especially when it involves 21 00:01:30,070 --> 00:01:33,690 the numpties IP stack is not easy when it's on Windows. 22 00:01:34,420 --> 00:01:39,700 The method I'm going to describe using virtual machines will work on most modern computers. 23 00:01:39,700 --> 00:01:45,760 And as of right now, if you want to do any deep learning stuff, whether that be with Fiinal or Tenzer 24 00:01:45,760 --> 00:01:47,980 flow, you cannot do this on windows. 25 00:01:48,400 --> 00:01:54,640 With that out of the way, I'm going to quickly go over which courses I've released so far or plan to 26 00:01:54,640 --> 00:01:58,600 release in the near future that do not require Ficano intensive flow. 27 00:01:58,900 --> 00:02:00,880 So it's possible to do on windows. 28 00:02:01,780 --> 00:02:07,360 With these in mind, you can decide if you want to install a virtual machine or not, but I would highly 29 00:02:07,360 --> 00:02:11,560 recommend it because it's free and everyone can follow the same instructions. 30 00:02:12,670 --> 00:02:19,030 So we've got linear regression in Python, logistic regression in Python, which are the prerequisites 31 00:02:19,030 --> 00:02:25,240 to deep learning Part one, and we have deep learning in Python, part one, which is mostly in dumpy 32 00:02:25,240 --> 00:02:26,630 and a little bit of tensor flow. 33 00:02:27,430 --> 00:02:32,260 We've got easy natural language processing in Python data analytics. 34 00:02:32,650 --> 00:02:38,710 Ask you all for newbies, beginners and marketers, cluster analysis and unsupervised machine learning 35 00:02:38,710 --> 00:02:41,950 in Python and unsupervised machine learning. 36 00:02:42,220 --> 00:02:44,110 Hidden Markov models in Python. 37 00:02:44,560 --> 00:02:47,730 This course is going to have a little bit of piano in it next. 38 00:02:47,740 --> 00:02:52,480 Here are some courses that depend heavily upon piano or tensor flow or both. 39 00:02:53,830 --> 00:02:59,830 We've got practical, deep learning in V.A. intensive, low, convolutional neural networks in Python, 40 00:03:00,280 --> 00:03:04,630 unsupervised, deep learning in Python and recurrent neural networks in Python. 41 00:03:05,200 --> 00:03:10,240 As you can see, a lot of interesting and complex stuff can be done in V.A. intensive flow. 42 00:03:11,200 --> 00:03:11,740 All right. 43 00:03:11,740 --> 00:03:15,530 So hopefully I've convinced you that using a virtual machine is a good idea. 44 00:03:16,270 --> 00:03:22,480 Windows is a great operating system, but it tends to not be as developer friendly since it tries to 45 00:03:22,480 --> 00:03:23,730 be more consumer friendly. 46 00:03:24,370 --> 00:03:27,360 Note that if you're on a Mac, this probably isn't necessary. 47 00:03:27,730 --> 00:03:35,110 You can just install Numpties Sipi Panda's matplotlib, Viento and Tenzer flow using easy install PIP. 48 00:03:36,170 --> 00:03:42,320 Sometimes this stuff can fail, depending on the many combinations of versions of each thing that are 49 00:03:42,320 --> 00:03:48,050 possible, but usually just Googling your error message will lead you to the right solution on stack 50 00:03:48,050 --> 00:03:48,580 overflow. 51 00:03:48,800 --> 00:03:55,940 If you're on a Mac, you can just do pseudo pip install, no Mississipi Python, Pendas, matplotlib 52 00:03:55,940 --> 00:03:56,540 and theno. 53 00:03:56,870 --> 00:04:01,220 Alternatively, you can use easy install, which might have a more recent version. 54 00:04:01,910 --> 00:04:07,370 You may need to use easy install to install PIP itself, which is just too easy and stop it. 55 00:04:07,940 --> 00:04:12,590 If you want to install Tenzer flow, just copy the command at Tancer Vlog. 56 00:04:12,740 --> 00:04:16,940 It's just a PIP install command that points to their custom installation location. 57 00:04:17,450 --> 00:04:22,820 I won't put it here since it corresponds to a specific version and that version may become out of date 58 00:04:22,820 --> 00:04:24,050 by the time you watch this. 59 00:04:24,620 --> 00:04:28,840 That is good news because the people working on Tenzer Flow are updating it all the time. 60 00:04:29,360 --> 00:04:29,810 All right. 61 00:04:29,820 --> 00:04:35,240 So if you've made it this far, that means you want to install a virtual machine with Linux on Windows 62 00:04:35,570 --> 00:04:40,610 or that you're already using Linux and you want to know what commands to use to install these libraries. 63 00:04:41,570 --> 00:04:47,960 We are going to need two things to start for this tutorial, virtual box and a lightweight version of 64 00:04:47,960 --> 00:04:48,470 Ubuntu. 65 00:04:49,010 --> 00:04:51,410 I would recommend Ubuntu or elevon, too. 66 00:04:51,830 --> 00:04:56,150 I'm going to use the 64 bit version of Ubuntu for this tutorial. 67 00:04:56,720 --> 00:04:59,570 So download these first and then return to the tutorial. 68 00:05:00,170 --> 00:05:00,590 All right. 69 00:05:00,590 --> 00:05:07,700 So now that you've got virtual box installed, we're going to create a new machine with 64 bit Ubuntu. 70 00:05:09,140 --> 00:05:12,050 So you want to hit new type in a name for your machine. 71 00:05:17,840 --> 00:05:19,700 And this stuff is already correct. 72 00:05:22,310 --> 00:05:23,620 I'm going to choose a. 73 00:05:25,150 --> 00:05:29,740 Two gigs of memory, you can choose more memory if your computer has more memory. 74 00:05:33,590 --> 00:05:35,840 I'm going to create a virtual hard disk now. 75 00:05:39,170 --> 00:05:43,970 I'm going to choose dynamically allocated and ECGs is good enough for this example. 76 00:05:50,000 --> 00:05:55,130 All right, so I'm going to go to settings if we go to storage. 77 00:05:57,170 --> 00:05:58,550 You can choose. 78 00:06:05,150 --> 00:06:13,630 The ISO file that you downloaded, so I'm going to load up the Ubuntu ISO that you downloaded from everyone 79 00:06:13,700 --> 00:06:14,270 to Whodunnit. 80 00:06:15,740 --> 00:06:16,160 All right. 81 00:06:16,160 --> 00:06:17,050 So OK. 82 00:06:19,260 --> 00:06:20,250 And it start. 83 00:06:22,430 --> 00:06:28,550 So it's going to take you through the installation of everyone to see you want to hit install. 84 00:06:35,600 --> 00:06:38,630 All right, so Element, who is going to take you through some prompts? 85 00:06:49,070 --> 00:06:52,490 All right, so you want to erase this, get install Ubuntu. 86 00:06:53,380 --> 00:06:58,330 And I'm not going to check any of these continue. 87 00:07:22,850 --> 00:07:27,110 All right, so once that's done, it's going to ask you to restart, so just restart now. 88 00:07:57,510 --> 00:08:03,870 All right, now that you're in the machine, what I always like to do, if you notice how this window 89 00:08:03,870 --> 00:08:13,530 is too big for my Mac window, you can make the enter window sizable by installing just additions. 90 00:08:13,530 --> 00:08:17,760 And this also lets you do useful things like cut and paste between machines. 91 00:08:23,980 --> 00:08:29,290 So you want to open a terminal, you go to system tools, select ELEX terminal. 92 00:08:34,810 --> 00:08:36,720 Now I'm going to cry into. 93 00:08:38,200 --> 00:08:38,980 That folder. 94 00:08:50,560 --> 00:08:58,910 Also, the correct command was Ceruti slash Vyborg Linux editions that run. 95 00:09:00,610 --> 00:09:05,570 Notice how there was something that failed in there, so we need to install Jack. 96 00:09:06,730 --> 00:09:09,970 So you want to run Sudo and get UPD? 97 00:09:13,020 --> 00:09:16,710 And then runs through app get upgrade. 98 00:09:24,620 --> 00:09:31,940 So the next thing is you want to sue, to get stall, build essential. 99 00:09:36,350 --> 00:09:44,240 All right, once you've done that, we can try to run Reebok's editions again so that sudo. 100 00:09:45,450 --> 00:09:46,620 Don't slash. 101 00:09:49,980 --> 00:09:51,720 If he barks Lennix. 102 00:09:54,160 --> 00:09:58,690 All right, so everything worked this time, so we're going to restart this machine. 103 00:10:07,220 --> 00:10:11,150 All right, so now the window is only as big as I want to drag it. 104 00:10:13,510 --> 00:10:21,580 OK, so now we can install the actual data science stuff, so you want to open again, Alex Terminal 105 00:10:22,210 --> 00:10:26,920 to a pseudo app to get update again? 106 00:10:35,830 --> 00:10:46,060 And you want to install it's a long list, so Python number, no Python Sibai. 107 00:10:49,200 --> 00:11:03,510 Python, matplotlib, ie, Python, Python, Pip, Python, Dev and Python set up tools. 108 00:11:07,060 --> 00:11:07,600 Yes. 109 00:11:12,590 --> 00:11:17,270 All right, so now that that's installed, you can test it out, can type in Python. 110 00:11:19,510 --> 00:11:23,110 So I python is open, import, vampy. 111 00:11:25,300 --> 00:11:30,940 Numpties working in Port Zippi Import Panda's. 112 00:11:32,900 --> 00:11:34,250 Right, we don't have pandas yet. 113 00:11:34,420 --> 00:11:38,950 We will install our next import matplotlib. 114 00:11:41,960 --> 00:11:44,610 So we have everything we've installed so far. 115 00:11:47,180 --> 00:11:48,800 So now we're going to install 116 00:11:51,290 --> 00:11:58,190 pandas and piano, so that's Pippin's still minus minus upgrade pandas the. 117 00:12:05,990 --> 00:12:09,680 All right, so now we've got Fiorino, the last thing we need is Tenzer flow. 118 00:12:11,500 --> 00:12:17,710 To get this, you guys want to go to the Tenzer Flow website and just grab the latest command since 119 00:12:17,710 --> 00:12:19,800 they're updating the package all the time. 120 00:12:21,980 --> 00:12:23,390 So let's open a browser. 121 00:12:27,850 --> 00:12:31,990 Let's search for install Tenzer flow. 122 00:12:48,680 --> 00:12:50,420 All right, you take this code. 123 00:12:54,840 --> 00:12:58,760 Copy and paste it in here. 124 00:13:02,780 --> 00:13:11,120 All right, now you've got V.A. intensive flow, you can test them out, go to GitHub, dot com slash 125 00:13:11,120 --> 00:13:16,490 lazy programmer slash machine learning examples. 126 00:13:32,650 --> 00:13:32,840 But. 127 00:13:40,570 --> 00:13:46,810 All right, so you need to get if you want to check out this code with get, so let's install it. 128 00:13:57,360 --> 00:13:59,520 All right, so let's run our clone command again. 129 00:14:06,150 --> 00:14:08,070 Let's try the HTTPS version. 130 00:14:17,780 --> 00:14:19,130 OK, so this one works. 131 00:14:23,760 --> 00:14:30,890 All right, so you see into machine learning examples go into an in class, too. 132 00:14:31,260 --> 00:14:33,720 So this has some introductory. 133 00:14:35,180 --> 00:14:43,190 Tenzer flaunt the anecdote, soldiers run Python, V.A. wound up high since this does not require any 134 00:14:43,190 --> 00:14:43,610 data. 135 00:14:48,300 --> 00:14:48,670 Cool. 136 00:14:48,690 --> 00:14:54,960 So it seems everything is working now let's try the Tenzer, for example, so it's Tenzer flow one. 137 00:15:01,790 --> 00:15:08,870 All right, so you want to make sure you install the correct answer flow, you want the CPU only version. 138 00:15:38,460 --> 00:15:41,640 Hopefully it just overrides the other version without any trouble. 139 00:15:43,680 --> 00:15:45,210 So let's try the example again. 140 00:15:50,630 --> 00:15:51,270 Super. 141 00:15:51,290 --> 00:15:52,700 So now everything is working. 142 00:15:54,030 --> 00:16:01,440 Now, if you want, there is a text editor that I highly recommend, it's called Sublime Text. 143 00:16:06,160 --> 00:16:07,570 So you had download. 144 00:16:09,090 --> 00:16:11,760 You go to Bunta 64 bit. 145 00:16:14,530 --> 00:16:15,460 You save this. 146 00:16:24,410 --> 00:16:26,450 And it will automatically be installed. 147 00:16:54,390 --> 00:16:59,190 All right, so now you have the exact same text editor that I use in my lectures. 148 00:17:05,160 --> 00:17:11,160 So you open machine learning examples, and this is all of our code.