How can i get free stuff? like phones and computers to test out or something?
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What laptop/computer should I purchase for deep learning? How much will it cost?
You will not be able to use just a laptop for efficiently training deep neural networks.However, if you want to train lots of small networks, or do some basic training before deploying your training script on a heavy machine, and are hell bent on buying a laptop for training, I’d suggest you buy a gaming laptop.Asus and Acer have good options here. You can run Linux on it like a pro.These have decent GPUs, and give you good performance for training small networks.This is more convenient than setting up an external GPU on another laptop.See this for Macs: Macs are now compatible with Nvidia's Pascal graphics, starting with the Titan XpBut then, I don’t think you should invest in a laptop for doing heavy machine learning.Build your own customised heavy duty machine. Here is an article I have shared multiple times about this topic: Build a Deep Learning Rig for $800 – Towards Data Science – MediumThere are various other good articles on Quora and elsewhere about setting up your own machine for doing deep learning.I believe that in today’s day and age, when GPUs are being upgraded so often, you don’t want to be left behind because you invested heavily in an older piece of hardware.Rent a suitable AWS instance. I have used this and find it one of the easiest services to configure and use.Rent a Google Cloud Platform instance. Have used it a little. Personally, I find the configuration and interface of this to be more complicated than than of AWS. But if Google churns out its TPUs (Tensor Processing Units) soon, I suspect that Google Cloud Platform will be the only service to host these devices for some time before other players in the industry can develop similar processors.Rent a Microsoft Azure instance. Don’t have experience in this area, so can’t say much.You only need a decent/average laptop now. You can develop your models on it, do a mock training on it, and then deploy it on the remote server.This is what I myself do to train neural nets. I design them on my MacBook Air, and then train it on an AWS instance. For guidance on how to do this, see this article which I wrote recently: Semantic Segmentation of Urban Street Scenes in Mathematica.
Help upgrading my PC?
How much FPS are you getting right now, and how many are you hoping to get? I have this same video board in my system, and it plays all games that I need it to play at pretty good FPS, at 1080p resolutions. If you're not playing 4K or AAA games, then you really don't need to get a 970 or 980, as those were designed to make 1440p gaming working. If you have a 1080p monitor, then no further benefits can be derived. Changing the processor is an option. If you want to go with a better processor, but not change the motherboard, then you should get the best processor that fits that same motherboard. The motherboard you have right now is either an FM2 or FM2+ motherboard, based on the fact that your current processor is designed for FM2. FM2 CPU's will fit in FM2+ motherboards, but not the other way around. So hopefully you have an FM2+ motherboard rather than the older FM2 one (do you know what motherboard model you have?), so you'll have a great range of parts you can install on it. The best parts that I'm thinking of is the Athlon X4 860K or 870K or 880K. Each of these requires an FM2+ motherboard. These processors are pretty cheap (less than $100), and extremely overclocking friendly, great little pocket rockets. You can replace the A8-6500 with one of these and you will probably realize a 10-15% improvement right away. However, I would suggest that if you're just looking for more FPS, then it's better if you just optimize your game settings. The easiest way to do that is to run the Nvidia Geforce Experience program that comes with your video card. It can scan your games and come up an optimized setting that will increase your FPS to the level you prefer, without changing anything, motherboard, processor or video card.