Neural-network Libraries

156 Components & Libraries

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Neural-network Libraries

pyclustering is a Python, C++ data mining library.

Each algorithm is implemented using Python and C/C++ language, if your platform is not supported then Python implementation is used, otherwise C/C++. Implementation can be chosen by ccore flag (by de…

Image Processing with Cellular Neural Networks in Python

The library is supported for Python >= 2.7 and Python >= 3.3. The python modules needed in order to use this library. Import module Initialize object General image processing Edge detection Gra…

The "Python Machine Learning (1st edition)" book code repository and info resource

What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning ... from theory to the actual code that you can directly put into…

An Open Source Machine Learning Framework for Everyone

TensorFlow was originally developed by researchers and engineers working within the Machine Intelligence team at Google Brain to conduct research in machine learning and neural networks. However, the…

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

If you prefer to use latest CNTK bits from master, use one of the CNTK nightly packages: You can learn more about using and contributing to CNTK with the following resources: Dear community, With our…

:books: [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics Fundamentals, Python Practices, NLP Application, etc. 💫 人工智能与深度学习实战，数理统计篇 | 机器学习篇 | 深度学习篇 | 自然语言处理篇 | 工具实践 Scikit & Tensoflow & PyTorch 篇 | 行业应用 & 课程笔记

在本系列中，你可能会接触到数据挖掘、机器学习、深度学习、自然语言处理、人工智能等很多的概念。值得说明的是，鉴于很多的算法实现是以文字结合代码介绍为最佳，因此工具实践篇中的大部分内容是以 Juypter Notebook 的形式放在该仓库中，并且在 Colab 中进行浏览、编辑与实验。 1956 年，几个计算机科学家相聚在达特茅斯会议，提出了“人工智能”的概念，梦想着用当时刚刚出现的计算机来构造…

:books: [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics Fundamentals, Python Practices, NLP Application, etc. 💫 人工智能与深度学习实战，数理统计篇 | 机器学习篇 | 深度学习篇 | 自然语言处理篇 | 工具实践 Scikit & Tensoflow & PyTorch 篇 | 行业应用 & 课程笔记

A flexible, high-performance serving system for machine learning models

To note a few features: The easiest and most straight-forward way of using TensorFlow Serving is with Docker images. We highly recommend this route unless you have specific needs that are not address…

Crossmodal Supervised Learning Toolkit using High-Performance Extreme Learning Machines over the audio-visual-textual data

Crossmodal Supervised Learning Toolkit using High-Performance Extreme Learning Machines over the audio-visual-textual data Parts of The Cerebrum: Cerebrum Crossmodal: Defines time based relations bet…

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

Use any of the following services. Next, run the following commands: Finally, start Jupyter: I recommend Python 3.7. If you follow the installation instructions above, that's the version you will get…

Image augmentation library in Python for machine learning.

Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independent, which is more convenient, allows for finer gr…

Super Resolution of picture images using deep learning

Super Resolution of picture images using deep learning. SeRanet upscales picture image size to x2. Before upscale Conventional method: image upscaled with lanczos method (with OpenCV library) Origina…

U-Net: Convolutional Networks for Biomedical Image Segmentation

R, Python and Mathematica Codes in Machine Learning, Deep Learning, Artificial Intelligence, NLP and Geolocation

I am a Data Scientist and I code in R, Python and Wolfram Mathematica. Here you will find some Machine Learning, Deep Learning, Natural Language Processing and Artificial Intelligence models I develo…

Notes, examples, and Python demos for the 2nd edition of the textbook "Machine Learning Refined" (published by Cambridge University Press).

We believe mastery of a certain machine learning concept/topic is achieved only when the answer to each of the following three questions is affirmative. Example ”roadmaps” shown below provide suggest…

Cluster images based on image content using a pre-trained deep neural network, optional time distance scaling and hierarchical clustering.

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMEN…

Collection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.

:computer: Learn to make machines learn so that you don't have to struggle to program them; The ultimate list

Machine Learning is a branch of Artificial Intelligence dedicated at making machines learn from observational data without being explicitly programmed. Machine learning and AI are not the same. Machi…

Email Spam-detection is an ANN app with TensorFlow. The idea is simple - given an email you’ve never seen before, determine whether or not that email is Spam

It is simple ,but very efficient as I reached 99.6% accuracy . In a python compatible environment, 1, invoke the script by command ./ExtractContent.py 2, input source directory -- where you store the…

A weekly workshop series at ITP to teach machine learning with a focus on deep learning

A weekly workshop series at NYU ITP to teach machine learning with a focus on deep learning

Python Machine Learning Algorithms

Programs can one of three implementations: The included programs are: Here are the descriptions of the above machine learning algorithms Because of the nature of training decision trees they can be p…

Neural networks toolbox focused on medical image analysis

A neural networks toolbox with a focus on medical image analysis in tensorflow/keras for now. If you use this code, please cite: If you are using any of the sparse/imputation functions, please cite:

Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

If you've finished the amazing introductory Machine Learning on Coursera by Prof. Andrew Ng, you probably got familiar with Octave/Matlab programming. With this repo, you can re-implement them in Pyt…

VizSec17: Web-based visualization tool for adversarial machine learning / LiveDemo

This is Andrew Norton's capstone research work. The goal is to perform a similar function to Google's TensorFlow Playground, but for evasion attacks in adversiaral machine learning. It is a web ser…

An interesting display of evolution through neural networks and a genetic algorithm

Bot evolution is an interesting display of evolution through neural networks and a genetic algorithm. Bot's have a field of vision represented by their antenna's. They are told if they "see" food in …

Deep Learning Toolkit for Medical Image Analysis

If you use DLTK in your work please refer to this citation for the current version: Setup a virtual environment and activate it. Although DLTK<=0.2.1 supports and python 2.7, we will not support i…