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Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

Arm NN ML Software. The code here is a read-only mirror of https://review.mlplatform.org/admin/repos/ml/armnn

A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG ecosystem.

Here we will keep track of the latest AI Game Development Tools, including LLM, Agent, Code, Writer, Image, Texture, Shader, 3D Model, Animation, Video, Audio, Music, Singing Voice and Analytics. ?

? Discover the Best in Custom GPT at OpenAI's GPT Store – Your Adventure Begins Here!

:octocat: A curated awesome list of AI Startups in India & Machine Learning Interview Guide. Feel free to contribute!

My Keras implementation of the Deep Semantic Similarity Model (DSSM)/Convolutional Latent Semantic Model (CLSM) described here: http://research.microsoft.com/pubs/226585/cikm2014_cdssm_final.pdf.

Free AI-Tips is a FREE Newsletter provided by Business Science. It comes with bite-sized Python AI for Business tutorials every week. Sign up here:

?This repo contains detailed notes and multiple projects implemented in Python related to AI and Finance. Follow the blog here: https://purvasingh.medium.com

Here you can find all the Tutorials for Haystack ?

Here lies the resources and topics necessary for the role of Data Scientist and Machine Learning

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic E

? A curated awesome list of Machine Learning Engineering resources. Feel free to contribute!

All NLP you Need Here. 目前包含15个NLP demo的pytorch实现（大量代码借鉴于其他开源项目，原先是自己玩的，后来干脆也开源出来）

Since the emergence of chatGPT in 2022, the acceleration of Large Language Model has become increasingly important. Here is a list of papers on accelerating LLMs, currently focusing mainly on inference acceleration, and related works will be gradually added in the future. Welcome contributions!

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract)

? 世界上覆盖最全的优秀Qwen提示语大全，欢迎贡献你的提示词。? The most comprehensive collection of excellent Qwen prompts in the world. Feel free to contribute your own prompts!

Hello Data Enthusiast! I will be updating my 100-day Journey here along with detailed Code Files Starting from Essential Libraries to Advanced Machine Learning and Deep Learning Algorithm Theory with Implementation. Save for Later ? Happy Learning :)

The CRF Layer was implemented by using Chainer 2.0. Please see more details here: https://createmomo.github.io/2017/09/12/CRF_Layer_on_the_Top_of_BiLSTM_1/

My (slightly modified) Keras implementation of the Recurrent Convolutional Neural Network (RCNN) described here: http://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/view/9745.