Neural Network Cars Mac OS

  1. Neural Network Cars Mac Os Download
  2. Neural Network Software
  3. Neural Networks Pdf
  4. Neural Network Cars Mac Os X

You can't use the CUDA package if you don't have an NVIDIA graphics card. So life will be much harder because OpenCL (which is your alternative GPU interface), is not as well supported. You can always try to use a remote server or an external GP. Networking - Managing a network of computers can be an involved process. Clonezilla SE lets you image and roll out multiple machines with ease. Fast multilayer perceptron neural network library for iOS and Mac OS X. MLPNeuralNet predicts new examples by trained neural network. It is built on top of the Apple's Accelerate Framework, using vectorized operations and hardware acceleration if available. . The Neural Engine from Apple is a neural network hardware integrated within the A-Series line of microprocessors since the A11 Bionic. A neural network hardware is an artificial intelligence accelerator designed for AI applications to include machine learning, as well as data processing for a more specific image and speech processing. MLPNeuralNet is a fast multilayer perceptron neural network library for iOS and Mac OS X. MLPNeuralNet predicts new examples through trained neural networks. It is built on top of Apple's Accelerate Framework using vectored operations and hardware acceleration (if available).

Fast multilayer perceptron neural network library for iOS and Mac OS X. MLPNeuralNet predicts new examples by trained neural network. It is built on top of the Apple's Accelerate Framework, using vectorized operations and hardware acceleration if available.

Neural Network Cars Mac Os Download

Why to choose it?

Imagine that you created a prediction model in Matlab (Python or R) and want to use it in iOS app. If that's the case, MLPNeuralNet is exactly what you need. It is designed to load and run models in forward propagation mode only.

Features:

  • classification, multiclass classification and regression output;
  • vectorized implementaion;
  • works with double precision;
  • multiple hidden layers or none (in that case it's same as logistic/linear regression)

Quick Example

Neural Network Software

Let's deploy a model for the AND function (conjunction) that works as follows (of course in real world you don't have to use neural net for this :)

X1X2Y
000
100
010
111

Our model has the following weights and network configuration:

Neural network cars mac os 11

Getting started

This instruction describes on how to install MLPNeuralNet using the CocoaPods. It is written for Xcode 5, using the iOS 7 SDK. If you are familiar with 3rd-party library management, just clone MLPNeuralNet repo on Github and import it to XCode directly as a subproject.

Neural Networks Pdf

Step 1. Install CocoaPods

CocoaPods is a dependency manager for Objective-C. Installing it is as easy as running the following commands in the terminal:

Neural Network Cars Mac Os X

Step 2. Create Podfile

List MLPNeuralNet as a dependenciy in a text file named Podfile in your Xcode project directory:

Step 3. Install MLPNeuralNet

Now you can install the dependencies in your project:

Make sure to always open the Xcode workspace (.xcworkspace) instead of the project file when building your project:

Step 4. Import MLPNeuralNet.h

#import 'MLPNeuralNet.h' to start working on your model. That's it!

Performance benchmark

In this test the neural net is grown layer by layer from 1 -> 1 configuration to 200 -> 200 -> 200 -> 1. At each step the output is calculated and benchmarked using random input vector and random weights. Total number of weights grows from 2 to 80601 accordingly. I understand the test is quite synthetic, but I hope it illustrates the performance. I will be happy if you can propse better one :)

Unit Tests

MLPNeuralNet includes a suite of unit tests in the MLPNeuralNetTests subdirectory. You can execute them via the 'MLPNeuralNet' scheme within Xcode.

Credits

  • MLPNeuralNet was inspired by Andrew Ng's course on Machine Learning.
  • Neural Network image was taken from Wikipedia Commons

Contact

Maintainer: Mykola Pavlov (me@nikolaypavlov.com).

Please let me know on how you use MLPNeuralNet for some real world problems.

License

MLPNeuralNet is available under the BSD license. See the LICENSE file for more info.

Written with StackEdit.