WEBVTT 00:00.980 --> 00:06.620 I'm so very happy that you've reached this epic moment in the course and that you're hanging in there. 00:06.620 --> 00:12.110 This is where things have gotten really crucial, and we're learning some of the most important things 00:12.110 --> 00:13.640 about building an LMS. 00:13.760 --> 00:20.930 And I'm I'm just very grateful that you've been staying along and hopefully enjoying it as much as I 00:20.960 --> 00:21.530 am. 00:21.770 --> 00:24.590 And yeah, the best is yet to come. 00:24.590 --> 00:28.490 So, uh, for today, it's going to be few slides. 00:28.490 --> 00:30.320 It's going to be all action. 00:30.410 --> 00:35.360 Uh, you're going to be looking at the actual run happening and weights and biases, and I'll be showing 00:35.360 --> 00:40.070 you the sorts of things to look for and how we can use weights and biases to get some intelligence about 00:40.070 --> 00:40.970 what's happening. 00:41.270 --> 00:46.610 Uh, I'm going to show you the Huggingface hub with models in it, and you get a sense of what's going 00:46.610 --> 00:47.210 on. 00:47.420 --> 00:54.050 Um, there's also one thing that's been on my mind that I mentioned last time that I, I don't want 00:54.050 --> 00:58.220 to be flippant about the importance of keeping costs low. 00:58.310 --> 01:04.190 The idea of this class is not to build up a big bill for you from, uh, from Google, who will happily 01:04.190 --> 01:07.190 take your, your money for for running their boxes. 01:07.310 --> 01:10.010 Um, I have a lot of fun running this training. 01:10.010 --> 01:12.740 It's, um, running the training process. 01:12.800 --> 01:19.820 Um, it's perfectly achievable to do that and get good results with the spending a matter of cents. 01:19.820 --> 01:23.810 And I did want to take just a quick moment to talk about that, because it's very important. 01:23.840 --> 01:28.340 And I don't want to, uh, lead you down the wrong path of thinking you have to spend lots of money 01:28.340 --> 01:32.180 to get good results and to learn particularly, which is the main objective here. 01:32.480 --> 01:35.540 Um, and so, in fact, we're going to start with that. 01:35.600 --> 01:42.530 Um, and I want to, uh, take you straight over to JupyterLab, not not to Google Colab, but JupyterLab, 01:42.530 --> 01:47.780 where I'm going to show you something to illustrate my point and to help set you up should you wish 01:47.780 --> 01:50.090 to be training at a lower cost.