LorenzoMainetti

LorenzoMainetti's Stars

• modelscope/modelscope

  ModelScope: bring the notion of Model-as-a-Service to life.

  Language:Python7k723

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook47.9k5.7k

• mindee/doctr

  docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.

  Language:Python3.9k447

• open-mmlab/mmocr

  OpenMMLab Text Detection, Recognition and Understanding Toolbox

  Language:Python4.4k754

• dangkhoasdc/awesome-ai-residency

  List of AI Residency Programs

  3.1k270

• JaidedAI/EasyOCR

  Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

  Language:Python24.7k3.2k

• DoubangoTelecom/ultimateALPR-SDK

  World's fastest ANPR / ALPR implementation for CPUs, GPUs, VPUs and NPUs using deep learning (Tensorflow, Tensorflow lite, TensorRT, OpenVX, OpenVINO). Multi-Charset (Latin, Korean, Chinese) & Multi-OS (Jetson, Android, Raspberry Pi, Linux, Windows) & Multi-Arch (ARM, x86).

  Language:C++629161

• Sinaptik-AI/pandas-ai

  Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.

  Language:Python13.6k1.3k

• langchain-ai/langchain

  🦜🔗 Build context-aware reasoning applications

  Language:Jupyter Notebook95.5k15.5k

• modernmt/modernmt

  Neural Adaptive Machine Translation that adapts to context and learns from corrections.

  Language:Java34271

• iryna-kondr/scikit-llm

  Seamlessly integrate LLMs into scikit-learn.

  Language:Python3.4k275

• jmschrei/avocado

  Avocado is a multi-scale deep tensor factorization model that learns a latent representation of the human epigenome and enables imputation of epigenomic experiments that have not yet been performed.

  Language:Jupyter Notebook11319

• STMicroelectronics/stm32ai-modelzoo

  AI Model Zoo for STM32 devices

  Language:C30778

• google-deepmind/deepmind-research

  This repository contains implementations and illustrative code to accompany DeepMind publications

  Language:Jupyter Notebook13.3k2.6k

• AlessandroAvi/Master_Thesis

  This repo contains the code developed for my master thesis

  Language:C61

• pavmassimo/TyBox

  Language:Jupyter Notebook111

• microsoft/EdgeML

  This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

  Language:C++1.6k371

• plotly/plotly.py

  The interactive graphing library for Python :sparkles: This project now includes Plotly Express!

  Language:Python16.4k2.6k

• matousc89/padasip

  Python Adaptive Signal Processing

  Language:Python30351

• tyiannak/amvoc

  A Python Tool for Analysis of Mouse Vocal Communication

  Language:Python142

• rchavezj/Cracking_The_Machine_Learning_Interview

  (Under Construction) I am currently writing a solution from the Medium article "Cracking the Machine Learning Interview," written by Subhrajit Roy. In the past year since the article went public, Subhrajit has only written down the questions with no update on the solutions. I plan on finishing the war. I may add more questions outside of the articles domain. No one else on the internet has written down a solution for machine learning interview, an opportunity I want to take advantage of.

  8731

• tyiannak/pyAudioAnalysis

  Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications

  Language:Python5.9k1.2k

• pratapkygo/noiseCancellationCarnaticMusic

  Various melodic noise filtering techniques viz. Adaptive Noise Cancellation, Spectral Methods and Deep Learning algorithms have been employed to filter music signals corrupted with additive Gaussian white noise. The noise reduction problem has been formulated as a filtering problem which is efficiently solved by using the LMS, NLMS and RLS methods in adaptive filtering and as a spectral problem solved using spectral subtraction and spectral gating techniques.

  Language:Jupyter Notebook81

• nebuly-ai/optimate

  A collection of libraries to optimise AI model performances

  Language:Python8.4k639

• carolbedoya/Beetle-Sounds-Inside-Wood

  This is the supplementary information (Code) for: "Experimental characterization and automatic identification of stridulatory sounds inside wood"

  2

• neetcode-gh/leetcode

  Leetcode solutions

  Language:JavaScript5.7k2.3k

• lorenmt/auto-lambda

  The Implementation of "Auto-Lambda: Disentangling Dynamic Task Relationships" [TMLR 2022].

  Language:Python12917

• median-research-group/LibMTL

  A PyTorch Library for Multi-Task Learning

  Language:Python2.1k192

• google-research/leaf-audio

  LEAF is a learnable alternative to audio features such as mel-filterbanks, that can be initialized as an approximation of mel-filterbanks, and then be trained for the task at hand, while using a very small number of parameters.

  Language:Python50152

• timsainb/noisereduce

  Noise reduction in python using spectral gating (speech, bioacoustics, audio, time-domain signals)

  Language:Jupyter Notebook1.5k231