Networks Libraries

115 Components & Libraries

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Networks Libraries

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…

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

An open-source python library built to empower developers to build applications and systems with self-contained Deep Learning and Computer Vision capabilities using simple and few lines of code. We t…

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…

Deep learning with satellite & aerial imagery

Extracting roads is challenging due to the occlusions caused by other objects and the complex traffic environment In instance segmentation, each individual 'instance' of a segmented area is given a u…

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…

Plain python implementations of basic machine learning algorithms

If you have a favorite algorithm that should be included or spot a mistake in one of the notebooks, please let me know by creating a new issue. See the LICENSE file for license rights and limitations…

Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

IPython Notebook(s) and other programming tools such as Torch/Lua/D lang in demonstrating deep learning functionality. Additional PyRo tutorials: IPython Notebook(s) demonstrating scikit-learn functi…

🛠 All-in-one web-based IDE specialized for machine learning and data science.

The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on you…

StellarGraph - Machine Learning on Graphs

Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can…

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

This repository contains all the code, notebooks and examples used in this book. We will also be adding bonus content here from time to time. So keep watching this space! Master the essential skills …

A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!

A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models! The concept of AI-Blocs is to have a simple scene with draggable objects that have scripts attached to…

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

Install PyGAD with the following command: The source code of the PyGAD' modules is found in the following GitHub projects: The next code implements all the callback functions to trace the execution o…

Platform for building access networks and modular network services

Magma is an open-source software platform that gives network operators an open, flexible and extendable mobile core network solution. Magma enables better connectivity by: The figure below shows the …

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…

CNN Image Retrieval in PyTorch: Training and evaluating CNNs for Image Retrieval in PyTorch

This is a Python toolbox that implements the training and testing of the approach described in our papers: This code implements: In order to run this toolbox you will need: For detailed explanation o…

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

Python interface for igraph

igraph is a library for creating and manipulating graphs. It is intended to be as powerful (ie. fast) as possible to enable the analysis of large graphs. This repository contains the source code to t…

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…

: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…

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

This book brings the fundamentals of Machine Learning to you, using tools and techniques used to solve real-world problems in Computer Vision, Natural Language Processing, and Time Series analysis. T…

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

Thank you for reading and for being a supporter of Towards AI! Big thank you to C4H3I LLC for sponsoring us in June, 2022!

A curated list of Best Artificial Intelligence Resources

Curso de Introducción a Machine Learning con Python

¿Te suenan las palabras Machine Learning o Data Scientist? ¿Te pica la curiosidad de para qué sirven estas técnicas o por qué empresas de todo el mundo pagan un sueldo de 120.000 hasta 200.000$ al añ…

Python library to easily log experiments and parallelize hyperparameter search for neural networks

Test tube is a python library to track and parallelize hyperparameter search for Deep Learning and ML experiments. It's framework agnostic and built on top of the python argparse API for ease of use.…

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…

Python script for illustrating Convolutional Neural Networks (CNN) using Keras-like model definitions

Python script for illustrating Convolutional Neural Networks (CNN). Inspired by the draw_convnet project [1]. python-pptx (if you want to save models as pptx) Keras (if you want to convert Keras sequ…

TypeDB-ML is the Machine Learning integrations library for TypeDB

You may find the following resources useful, particularly to understand why TypeDB-ML started: Python >= 3.7.x It's expected that you will use Pip to install, but should you need to make your own …

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