1 00:00:11,610 --> 00:00:17,230 Hey guys in this lecture I'm going to show you how to set up your development environment so that you 2 00:00:17,230 --> 00:00:21,150 can follow along in these courses. 3 00:00:21,160 --> 00:00:28,010 First let's talk about operating systems the three big ones are Windows Linux and Mac. 4 00:00:28,150 --> 00:00:32,200 Most but not all of my courses are part of the Deep Learning series. 5 00:00:32,410 --> 00:00:38,590 Eventually the deep learning models were going to build will become so complex that we will need specialized 6 00:00:38,590 --> 00:00:42,830 libraries like Fino and tensor flow to implement them. 7 00:00:42,850 --> 00:00:48,610 Now as of today piano intensive flow are not officially supported on Windows. 8 00:00:48,790 --> 00:00:54,160 So if you are interested in deep learning you will discover pretty soon that there is not much you can 9 00:00:54,160 --> 00:00:56,280 do without a ton of work. 10 00:00:56,680 --> 00:01:02,440 Even working with non GP you enabled libraries like Nam pi and Matt Platt lib can be a challenge. 11 00:01:02,590 --> 00:01:08,870 But these are at least possible on windows if you really must use windows and have your python environment 12 00:01:08,870 --> 00:01:14,630 inside windows and you don't want to try the virtual machine method which I'm going to discuss next. 13 00:01:14,630 --> 00:01:18,950 Then one good library I know of is called Anaconda. 14 00:01:18,950 --> 00:01:21,500 You can get Anaconda at continuum. 15 00:01:21,500 --> 00:01:24,650 I O slash downloads. 16 00:01:24,650 --> 00:01:30,380 I can't vouch for this one hundred percent because I haven't used it myself but I've known others who 17 00:01:30,380 --> 00:01:32,720 have found it at least usable. 18 00:01:32,720 --> 00:01:34,850 Now I'm telling you this from experience. 19 00:01:34,910 --> 00:01:40,580 I've worked with a ton of clients one on one and Python development especially when it involves the 20 00:01:40,580 --> 00:01:44,680 number pi side pi stack is not easy when it's on Windows. 21 00:01:44,900 --> 00:01:50,750 The method I'm going to describe using virtual machines will work on most modern computers and as of 22 00:01:50,750 --> 00:01:57,410 right now if you want to do any deep learning stuff whether that be with V.A. or tensor flow you cannot 23 00:01:57,410 --> 00:01:58,680 do this on Windows. 24 00:01:58,910 --> 00:02:05,060 With that out of the way I'm going to quickly go over which courses I've released so far or plan to 25 00:02:05,060 --> 00:02:11,270 release in the near future that do not require V.A. intensive flow so it's possible to do on windows 26 00:02:12,270 --> 00:02:17,760 with these in mind you can decide if you want to install a virtual machine or not but I would highly 27 00:02:17,760 --> 00:02:25,030 recommend it because it's free and everyone can follow the same instructions so we've got linear regression 28 00:02:25,030 --> 00:02:31,780 in Python logistic regression in Python which are the prerequisites to deep learning part one. 29 00:02:31,900 --> 00:02:37,030 We have deep learning in Python part 1 which is mostly in number pi and a little bit of tensor flow 30 00:02:37,930 --> 00:02:43,050 we've got easy natural language processing and Python data analytics. 31 00:02:43,170 --> 00:02:49,210 Ask you all for newbies beginners and marketers cluster analysis an unsupervised machine learning in 32 00:02:49,210 --> 00:02:54,900 Python and unsupervised machine learning hit and Markoff models in python. 33 00:02:55,060 --> 00:02:58,040 This course is going to have a little bit of piano in it next. 34 00:02:58,180 --> 00:03:02,940 Here are some courses that depend heavily upon piano or tensor flow or both. 35 00:03:04,300 --> 00:03:11,590 We've got practical deep learning in piano intensive flow convolution on neural networks in Python unsupervised 36 00:03:11,590 --> 00:03:15,510 deep learning in Python and recurrent neural networks in Python. 37 00:03:15,730 --> 00:03:21,720 As you can see a lot of interesting and complex stuff can be done in Vienna intensive flow. 38 00:03:21,720 --> 00:03:22,150 All right. 39 00:03:22,150 --> 00:03:26,740 So hopefully I've convinced you that using a virtual machine is a good idea. 40 00:03:26,740 --> 00:03:33,040 Windows is a great operating system but it tends to not be as developer friendly since it tries to be 41 00:03:33,040 --> 00:03:34,840 more consumer friendly. 42 00:03:34,840 --> 00:03:38,160 Note that if you're on a Mac this probably isn't necessary. 43 00:03:38,230 --> 00:03:45,490 You can just install num pie side by Panda's Matlab lib piano and tensor flow using easy installer Pip 44 00:03:46,640 --> 00:03:52,700 sometimes this stuff can fail depending on the many combinations of versions of each thing that are 45 00:03:52,700 --> 00:03:59,290 possible but usually just googling your error message will lead you to the right solution on Stack Overflow. 46 00:03:59,330 --> 00:04:06,920 If you're on a Mac you can just do pseudo pip install num by Skype I Python Panda's map live in Vienna. 47 00:04:07,340 --> 00:04:13,670 Alternatively you can use easy install which might have a more recent version you may need to use easy 48 00:04:13,670 --> 00:04:20,380 install to install Pip itself which is just pseudo easy install Pip if you want to install tensor flow. 49 00:04:20,570 --> 00:04:23,210 Just copy the command at tensor flow dawg. 50 00:04:23,270 --> 00:04:27,950 It's just a pip install command that points to their custom installation location. 51 00:04:27,950 --> 00:04:33,230 I won't put it here since it corresponds to a specific version and that version may become out of date 52 00:04:33,230 --> 00:04:35,040 by the time you watch this. 53 00:04:35,090 --> 00:04:39,780 That is good news because the people working on intensive flow are updating it all the time. 54 00:04:39,890 --> 00:04:44,900 All right so if you've made it this far that means you want to install a virtual machine with Linux 55 00:04:44,930 --> 00:04:50,450 on Windows or that you're already using Linux and you want to know what commands to use to install these 56 00:04:50,450 --> 00:04:51,950 libraries. 57 00:04:52,030 --> 00:04:55,700 We are going to need two things to start for this tutorial. 58 00:04:55,700 --> 00:04:59,240 Virtual Box and a lightweight version of Ubuntu. 59 00:04:59,540 --> 00:05:02,230 I would recommend X Ubuntu or element two. 60 00:05:02,360 --> 00:05:09,170 I'm going to use the 64 bit version of L2 Bantu for this tutorial so download these first and then return 61 00:05:09,170 --> 00:05:10,670 to the tutorial. 62 00:05:10,700 --> 00:05:11,000 All right. 63 00:05:11,030 --> 00:05:18,310 So now that you've got virtual box installed we're going to create a new machine with 64 bit L2 buttons. 64 00:05:19,150 --> 00:05:22,460 So you want to hit new type in a name for your machine 65 00:05:28,350 --> 00:05:30,220 and this stuff is already correct. 66 00:05:32,790 --> 00:05:36,770 I'm going to choose two gigs of memory. 67 00:05:36,830 --> 00:05:40,130 You can choose more memory if your computer has more memory 68 00:05:44,080 --> 00:05:45,860 I'm going to create a virtual hard disk. 69 00:05:45,860 --> 00:05:46,220 Now 70 00:05:49,700 --> 00:05:54,380 I'm going to choose dynamically allocated and 8 gigs is good enough for this example 71 00:06:00,530 --> 00:06:03,790 all right so I'm going to go to settings. 72 00:06:04,230 --> 00:06:09,020 If we go to storage you can choose 73 00:06:15,620 --> 00:06:18,260 the iso file that you downloaded. 74 00:06:18,260 --> 00:06:26,570 So I'm gonna load up the Blue Band to ISO that you downloaded from every bunch you've done it all right. 75 00:06:26,600 --> 00:06:26,920 So here. 76 00:06:26,930 --> 00:06:45,730 OK and it start so it's gonna take you through the installation of L1 to see you want to hit install. 77 00:06:46,120 --> 00:06:46,480 All right. 78 00:06:46,510 --> 00:06:49,060 So element who is gonna take you through some prompts 79 00:06:59,660 --> 00:06:59,990 right. 80 00:06:59,990 --> 00:07:01,610 So you want to erase this. 81 00:07:01,610 --> 00:07:07,670 Get install Ubuntu and I'm not going to check any of these. 82 00:07:08,020 --> 00:07:33,130 Continue. 83 00:07:33,330 --> 00:07:33,650 All right. 84 00:07:33,650 --> 00:07:35,860 So once that's done it's going to ask you to restart. 85 00:07:36,050 --> 00:07:37,190 So just it restart. 86 00:07:37,190 --> 00:07:37,460 Now 87 00:08:08,050 --> 00:08:14,860 all right now that you're in the machine what I always like to do if you notice how this window is too 88 00:08:14,860 --> 00:08:23,960 big for my Mac window you can make the inner window re sizable by installing guest editions. 89 00:08:23,970 --> 00:08:33,720 And this also lets you do useful things like cut and paste between machines. 90 00:08:34,410 --> 00:08:45,190 So you want to open a terminal you go to System Tools select El X terminal. 91 00:08:45,310 --> 00:08:49,390 Now when a city into that folder 92 00:09:00,970 --> 00:09:13,420 goes to the correct command was suru dot slash v box Linux editions that run notice how there was something 93 00:09:13,420 --> 00:09:14,230 that failed in there. 94 00:09:14,260 --> 00:09:17,170 So we need to install GCSE. 95 00:09:17,170 --> 00:09:20,320 So you want to run sudo apt get update 96 00:09:23,540 --> 00:09:27,110 and then run sudo apt get upgrade 97 00:09:35,100 --> 00:09:42,330 so the next thing is you want to suru apt get install build central 98 00:09:46,710 --> 00:09:57,030 all right once you've done that we can try to run Redbox box editions again so that pseudo dot slash 99 00:10:00,450 --> 00:10:04,610 v box Linux. 100 00:10:04,670 --> 00:10:05,000 All right. 101 00:10:05,030 --> 00:10:17,640 So everything work this time so we're going to restart this machine. 102 00:10:17,730 --> 00:10:18,090 All right. 103 00:10:18,120 --> 00:10:24,130 So now the window is only as big as I want to drag it. 104 00:10:24,370 --> 00:10:29,390 So now we can install the actual data science stuff. 105 00:10:29,620 --> 00:10:46,150 So you want to open again Alex Terminal 2 a Sue apps get update again. 106 00:10:46,340 --> 00:10:47,650 Now you want to install 107 00:10:51,180 --> 00:10:56,440 so long lists so fell num pi Python side by 108 00:10:59,280 --> 00:11:13,950 pi fine matte plot lib I python I found Pip python dev and Python set up tools 109 00:11:17,080 --> 00:11:17,430 sit. 110 00:11:17,490 --> 00:11:18,280 Yes. 111 00:11:23,150 --> 00:11:23,420 All right. 112 00:11:23,420 --> 00:11:26,160 So now that that's installed you can test it out. 113 00:11:26,300 --> 00:11:32,470 Can type in a python so I python is open. 114 00:11:32,470 --> 00:11:43,570 Import num pi then PIs working import side by import pandas right. 115 00:11:43,570 --> 00:11:44,950 We don't have pandas yet. 116 00:11:44,950 --> 00:11:49,350 We will install the next import apply live 117 00:11:52,060 --> 00:11:55,000 call so we have everything we've installed so far. 118 00:11:57,630 --> 00:11:59,220 So now we're going to install 119 00:12:01,770 --> 00:12:08,880 pandas MVNO so that it's pip install minus minus upgrade pandas the ANO 120 00:12:16,480 --> 00:12:16,830 All right. 121 00:12:16,860 --> 00:12:18,060 So now we've got Fiona. 122 00:12:18,060 --> 00:12:22,690 The last thing we need is tensor flow to get this. 123 00:12:22,690 --> 00:12:29,050 You guys wanna go to the tensor flow Web site and just grab the latest command since they're updating 124 00:12:29,050 --> 00:12:30,540 the package all the time. 125 00:12:32,420 --> 00:12:33,770 So let's open a browser 126 00:12:38,130 --> 00:12:42,390 and let's search for install tensor flow 127 00:12:58,980 --> 00:12:59,820 all right. 128 00:12:59,870 --> 00:13:00,830 Take this code 129 00:13:05,280 --> 00:13:09,170 copy and paste it in here 130 00:13:13,280 --> 00:13:13,610 all right. 131 00:13:13,620 --> 00:13:23,430 Now you've got V.A. intensive flow you can test them out to get her dot com slash lazy programmer slash 132 00:13:23,430 --> 00:13:26,940 machine learning examples 133 00:13:51,100 --> 00:13:51,380 all right. 134 00:13:51,410 --> 00:13:57,170 So you need to get if you want to check out this code with get so let's install get 135 00:14:07,900 --> 00:14:09,920 all right so let's run our clone command again. 136 00:14:16,430 --> 00:14:18,470 Let's try the CTP s version 137 00:14:28,300 --> 00:14:28,550 OK. 138 00:14:28,570 --> 00:14:29,530 So this one works 139 00:14:34,280 --> 00:14:34,610 all right. 140 00:14:34,630 --> 00:14:41,400 So you see into the machine learning examples go into and in class too. 141 00:14:41,720 --> 00:14:47,580 So this has some introductory tensor flow on the ANO code. 142 00:14:47,720 --> 00:14:53,960 So just run Python free and or one up high since this does not require any data 143 00:14:58,760 --> 00:14:59,090 cool. 144 00:14:59,100 --> 00:15:01,590 So it seems everything is working. 145 00:15:01,590 --> 00:15:03,810 Now let's try the tensor flow example. 146 00:15:03,930 --> 00:15:05,370 So it's tensor flow one 147 00:15:12,320 --> 00:15:12,600 all right. 148 00:15:12,600 --> 00:15:17,160 So you want to make sure you install the correct tensor flow. 149 00:15:17,160 --> 00:15:19,260 You want the ECP you only version 150 00:15:48,970 --> 00:15:53,550 hopefully it just overrides the other version without any trouble. 151 00:15:54,100 --> 00:15:55,570 So let's try the example again 152 00:16:01,130 --> 00:16:01,720 super. 153 00:16:01,730 --> 00:16:04,420 So now everything is working. 154 00:16:04,560 --> 00:16:05,310 Now if you want. 155 00:16:05,330 --> 00:16:10,210 There is a text editor that I highly recommend. 156 00:16:10,350 --> 00:16:11,850 It's called Sublime Text 157 00:16:16,600 --> 00:16:22,080 so you download you go to Ubuntu 64 bit 158 00:16:24,980 --> 00:16:25,880 you save this 159 00:16:34,910 --> 00:16:36,860 and it will automatically be installed 160 00:17:04,860 --> 00:17:05,190 all right. 161 00:17:05,200 --> 00:17:09,610 So now you have the exact same text editor that I use in my lectures 162 00:17:15,580 --> 00:17:21,570 see you open machine learning examples and this is all of our code.