Search Results for "x-rite"
Sort By:
Showing 23 open source projects for "x-rite"
View related business solutions-
New Plans, same great Auth0 | Auth0 by OktaIn our new Free Plan, you'll receive more MAUs than ever. You'll also be able to add Passwordless authentication, use your own custom domain, and more. Our expanded Paid Plans include increased connections, more MFA offerings, and more. Check out what's new.
-
Free CRM Software With Something for EveryoneThink CRM software is just about contact management? Think again. HubSpot CRM has free tools for everyone on your team, and it’s 100% free. Here’s how our free CRM solution makes your job easier.
-
1
x-transformers
A simple but complete full-attention transformer
A simple but complete full-attention transformer with a set of promising experimental features from various papers. Proposes adding learned memory key/values prior to attending. They were able to remove feedforwards altogether and attain a similar performance to the original transformers. I have found that keeping the feedforwards and adding the memory key/values leads to even better performance. Proposes adding learned tokens, akin to CLS tokens, named memory tokens, that is passed through... -
2
Transformer Reinforcement Learning X
A repo for distributed training of language models with Reinforcement
trlX is a distributed training framework designed from the ground up to focus on fine-tuning large language models with reinforcement learning using either a provided reward function or a reward-labeled dataset. Training support for Hugging Face models is provided by Accelerate-backed trainers, allowing users to fine-tune causal and T5-based language models of up to 20B parameters, such as facebook/opt-6.7b, EleutherAI/gpt-neox-20b, and google/flan-t5-xxl. For models beyond 20B parameters,... -
3
Sockeye
Sequence-to-sequence framework, focused on Neural Machine Translation
... to sockeye-dev-at-amazon-dot-com. Developers may be interested in our developer guidelines. Starting with version 3.0.0, Sockeye is also based on PyTorch. We maintain backwards compatibility with MXNet models of version 2.3.x with 3.0.x. If MXNet 2.x is installed, Sockeye can run both with PyTorch or MXNet. All models trained with 2.3.x (using MXNet) can be converted to models running with PyTorch using the converter CLI (sockeye.mx_to_pt). -
4
tf2onnx
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
tf2onnx converts TensorFlow (tf-1.x or tf-2.x), keras, tensorflow.js and tflite models to ONNX via command line or python API. Note: tensorflow.js support was just added. While we tested it with many tfjs models from tfhub, it should be considered experimental. TensorFlow has many more ops than ONNX and occasionally mapping a model to ONNX creates issues. tf2onnx will use the ONNX version installed on your system and installs the latest ONNX version if none is found. We support and test ONNX... -
Bright Data - All in One Platform for Proxies and Web ScrapingBright Data offers the highest quality proxies with automated session management, IP rotation, and advanced web unlocking technology. Enjoy reliable, fast performance with easy integration, a user-friendly dashboard, and enterprise-grade scaling. Powered by ethically-sourced residential IPs for seamless web scraping.
-
5
EconML
Python Package for ML-Based Heterogeneous Treatment Effects Estimation
... personalized decision scenarios is the estimation of heterogeneous treatment effects: what is the causal effect of an intervention on an outcome of interest for a sample with a particular set of features? In a nutshell, this toolkit is designed to measure the causal effect of some treatment variable(s) T on an outcome variable Y, controlling for a set of features X, W and how does that effect vary as a function of X. -
6
PyTensor
Python library for defining and optimizing mathematical expressions
PyTensor is a fork of Aesara, a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays. PyTensor is based on Theano, which has been powering large-scale computationally intensive scientific investigations since 2007. A hackable, pure-Python codebase. Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that... -
7
TensorFlow Addons
Useful extra functionality for TensorFlow 2.x maintained by SIG-addons
... of the community). The maintainers of TensorFlow Addons can be found in the CODEOWNERS file of the repo. This file is parsed and pull requests will automatically tag the owners using a bot. If you would like to maintain something, please feel free to submit a PR. We encourage multiple owners for all submodules. TensorFlow Addons is actively working towards forward compatibility with TensorFlow 2.x. -
8
DeepCTR
Package of deep-learning based CTR models
DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based... -
9
Causal ML
Uplift modeling and causal inference with machine learning algorithms
Causal ML is a Python package that provides a suite of uplift modeling and causal inference methods using machine learning algorithms based on recent research [1]. It provides a standard interface that allows users to estimate the Conditional Average Treatment Effect (CATE) or Individual Treatment Effect (ITE) from experimental or observational data. Essentially, it estimates the causal impact of intervention T on outcome Y for users with observed features X, without strong assumptions... -
Cybersecurity Management Software for MSPsDefine and Deliver Comprehensive Cybersecurity Services. Security threats continue to grow, and your clients are most likely at risk. Small- to medium-sized businesses (SMBs) are targeted by 64% of all cyberattacks, and 62% of them admit lacking in-house expertise to deal with security issues. Now technology solution providers (TSPs) are a prime target. Enter ConnectWise Cybersecurity Management (formerly ConnectWise Fortify) — the advanced cybersecurity solution you need to deliver the managed detection and response protection your clients require. Whether you’re talking to prospects or clients, we provide you with the right insights and data to support your cybersecurity conversation. From client-facing reports to technical guidance, we reduce the noise by guiding you through what’s really needed to demonstrate the value of enhanced strategy.
-
10
ktrain
ktrain is a Python library that makes deep learning AI more accessible
... of code, ktrain allows you to easily and quickly. ktrain purposely pins to a lower version of transformers to include support for older versions of TensorFlow. If you need a newer version of transformers, it is usually safe for you to upgrade transformers, as long as you do it after installing ktrain. As of v0.30.x, TensorFlow installation is optional and only required if training neural networks. -
11
The SpeechBrain Toolkit
A PyTorch-based Speech Toolkit
... in a wide variety of realistic applications. SpeechBrain provides different models for speaker recognition, including X-vector, ECAPA-TDNN, PLDA, and contrastive learning. Spectral masking, spectral mapping, and time-domain enhancement are different methods already available within SpeechBrain. Separation methods such as Conv-TasNet, DualPath RNN, and SepFormer are implemented as well. SpeechBrain provides efficient and GPU-friendly speech augmentation pipelines and acoustic features extraction. -
12
TensorFlow Model Garden
Models and examples built with TensorFlow
... are suitable. A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. It seamlessly integrates with tf.distribute and supports running on different device types (CPU, GPU, and TPU). -
13
Conscious Artificial Intelligence
It's possible for machines to become self-aware.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3... -
14
Interpretable machine learning
Book about interpretable machine learning
This book is about interpretable machine learning. Machine learning is being built into many products and processes of our daily lives, yet decisions made by machines don't automatically come with an explanation. An explanation increases the trust in the decision and in the machine learning model. As the programmer of an algorithm you want to know whether you can trust the learned model. Did it learn generalizable features? Or are there some odd artifacts in the training data which the... -
15
cintruder
CIntruder - OCR Bruteforcing Toolkit
Captcha Intruder is an automatic pentesting tool to bypass captchas. -> CIntruder-v0.4 (.zip) -> md5 = 6326ab514e329e4ccd5e1533d5d53967 -> CIntruder-v0.4 (.tar.gz) ->md5 = 2256fccac505064f3b84ee2c43921a68 -------------------------------------------- -
16
NeuroNER
Named-entity recognition using neural networks
Named-entity recognition (NER) aims at identifying entities of interest in the text, such as location, organization and temporal expression. Identified entities can be used in various downstream applications such as patient note de-identification and information extraction systems. They can also be used as features for machine learning systems for other natural language processing tasks. Leverages the state-of-the-art prediction capabilities of neural networks (a.k.a. "deep learning") Is... -
17
Deepo
Set up deep learning environment in a single command line
Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment, supports almost all commonly used deep learning frameworks, supports GPU acceleration (CUDA and cuDNN included), also works in CPU-only mode, and works on Linux (CPU version/GPU version), Windows (CPU version) and OS X (CPU version). Their Dockerfile generator that allows you to customize your own environment with Lego-like modules, and automatically resolves the dependencies for you... -
18
auto_ml
Automated machine learning for analytics & production
... trying to predict. Pass all that into auto_ml, and see what happens! You can pass in your own function to perform feature engineering on the data. This will be called as the first step in the pipeline that auto_ml builds out. You will be passed the entire X dataset (not the y dataset), and are expected to return the entire X dataset. The advantage of including it in the pipeline is that it will then be applied to any data you want predictions on later. -
19
HYBRYD
Library written in C with Python API for IPv6 networking
This project is a rewritten of an initial project that I've called GLUE and created in 2005. I'm trying to readapt it for Python 2.7.3 and GCC 4.6.3 The library has to be build as a simple Python extension using >python setup.py install and allows to create different kind of servers, clients or hybryds (clients-servers) over (TCP/UDP) using the Ipv6 Protocol. The architecture of the code is based on brain architecture. Will put an IPv6 adress active available as soon as... -
20
FineSplice
Enhanced splice junction detection and estimation from RNA-Seq data
...-supervised anomaly detection strategy based on logistic regression. Multiple mapping reads with a unique location after filtering are rescued and reallocated to the most reliable candidate location. FineSplice requires Python 2.x (>= 2.6) with the following modules installed: pysam (http://code.google.com/p/pysam/) and scikit-learn (http://scikit-learn.org/). For further details check out our publication: Nucl. Acids Res. (2014) doi: 10.1093/nar/gku166 -
21
mlpy
Machine Learning Python
mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X. -
22
Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
-
23
The intention of this project is to give all serious users of the SNNS a place where they find a bugfix and patch management and where they get useful information about the SNNS.
- Previous
- You're on page 1
- Next