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Unity3D Machine Learning - Setting up the environment & Tensorflow for AgentML on Windows10

@machinelearnbot

I'm extremely excited about the new Unity3D Machine Learning functionality that's being added. Setting it up was a little painful though, so I wanted to share the steps I followed, with the specific versions that work (I tried a whole lot and nothing else worked). In this guide, I'll show you everything you need to get setup and ready to start with the 3D ball example. You'll need to download CUDA 8.0.61 for this to work. Close any open Unity and Visual Studio instances (you'll have to restart the installer if you don't do this first) You'll need to create an NVIDIA account and log in to download the library.


Installing TensorFlow on Windows

#artificialintelligence

If you have a suitable screen card on your computer, you should set up GPU because processes will proceed more effectly and fastly. If you have a screen card that is different from NVIDIA, you need to set up for CPU. Because only NVIDIA screen cards is supported for GPU. You can set up GPU for Tensorflow, if CUDA compute capability of your screen card release is bigger than 3.5 . For instance, my screen card is NVIDIA GEFORCE 930M and its release seems 5.0, so I can set up GPU easily.


Installing CUDA and cuDNN on windows 10 – akshay sinha – Medium

#artificialintelligence

This is an how-to guide for someone who is trying to figure our, how to install CUDA and cuDNN on windows to be used with tensorflow. It should be noted that at the time of writing this, tensor flow is supporting only upto CUDA version 9.0 and corresponding cuDNN libraries so please don't download CUDA 9.2. Please note if your connection permits, please download the local version. That saves you from sitting around waiting for download to finish at the installation time. The download should be 1.4 G. Once the download finishes, launch the installer and follow the defaults.


Installing CUDA and cuDNN on windows 10 – akshay sinha – Medium

#artificialintelligence

This is an how-to guide for someone who is trying to figure our, how to install CUDA and cuDNN on windows to be used with tensorflow. It should be noted that at the time of writing this, tensor flow is supporting only upto CUDA version 9.0 and corresponding cuDNN libraries so please don't download CUDA 9.2. Please note if your connection permits, please download the local version. That saves you from sitting around waiting for download to finish at the installation time. The download should be 1.4 G. Once the download finishes, launch the installer and follow the defaults.


philferriere/dlwin

#artificialintelligence

There are certainly a lot of guides to assist you build great deep learning (DL) setups on Linux or Mac OS (including with Tensorflow which, unfortunately, as of this posting, cannot be easily installed on Windows), but few care about building an efficient Windows 10-native setup. Most focus on running an Ubuntu VM hosted on Windows or using Docker, unnecessary - and ultimately sub-optimal - steps. We also found enough misguiding/deprecated information out there to make it worthwhile putting together a step-by-step guide for the latest stable versions of Keras, Tensorflow, CNTK, MXNet, and PyTorch. Used either together (e.g., Keras with Tensorflow backend), or independently -- PyTorch cannot be used as a Keras backend, TensorFlow can be used on its own -- they make for some of the most powerful deep learning python libraries to work natively on Windows. If you must run your DL setup on Windows 10, then the information contained here will hopefully be useful to you.