2410 Repositories
Python Machine-Intelligence-Lab-CS305 Libraries
Code reimplementation of some papers published in SAIL-Lab
SAIL SAIL-Lab统一代码库 Motivation 创建这个项目的动机最早来源于实验室组内成员相互Debug代码的时候遇到的麻烦。
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
I-Spy is a discord and twitter bot 🤖 that keeps a check on usage foul language, hate-speech and NSFW contents
I-Spy is a discord and twitter bot 🤖 that keeps a check on usage foul language, hate-speech and NSFW contents. It is the one stop solution to monitor your discord servers and twitter handles against community demons by offering content moderation.
Lab course materials for IEMBA 8/9 course "Coding and Artificial Intelligence"
IEMBA 8/9 - Coding and Artificial Intelligence Dear IEMBA 8/9 students, welcome to our IEMBA 8/9 elective course Coding and Artificial Intelligence, t
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
Knowledge Informed Machine Learning using a Weibull-based Loss Function Exploring the concept of knowledge-informed machine learning with the use of a
Repository for the AugmentedPCA Python package.
Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
Machine Learning Model deployment for Container (TensorFlow Serving)
try_tf_serving ├───dataset │ ├───testing │ │ ├───paper │ │ ├───rock │ │ └───scissors │ └───training │ ├───paper │ ├───rock
GANfolk: Using AI to create portraits of fictional people to sell as NFTs
GANfolk are AI-generated renderings of fictional people. Each image in the collection was created by a pair of Generative Adversarial Networks (GANs) with names and backstories also created with AI. The GANs were trained using portraits from artists like Renoir, Turner, and Modigliani in addition to open-source, modern photos.
Local cross-platform machine translation GUI, based on CTranslate2
DesktopTranslator Local cross-platform machine translation GUI, based on CTranslate2 Download Windows Installer You can either download a ready-made W
Machine learning and Deep learning models, deploy on telegram (the best social media)
Semi Intelligent BOT The project involves : Classifying fake news Classifying objects such as aeroplane, automobile, bird, cat, deer, dog, frog, horse
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
An-Introduction-to-Statistical-Learning This repository contains the exercises and its solution contained in the book An Introduction to Statistical L
🎁 3,000,000+ Unsplash images made available for research and machine learning
The Unsplash Dataset The Unsplash Dataset is made up of over 250,000+ contributing global photographers and data sourced from hundreds of millions of
Machine Learning Course with Python:
A Machine Learning Course with Python Table of Contents Download Free Deep Learning Resource Guide Slack Group Introduction Motivation Machine Learnin
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥
TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens
Trax — Deep Learning with Clear Code and Speed
Trax — Deep Learning with Clear Code and Speed Trax is an end-to-end library for deep learning that focuses on clear code and speed. It is actively us
A collection of machine learning examples and tutorials.
machine_learning_examples A collection of machine learning examples and tutorials.
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In
Natural Language Processing Best Practices & Examples
NLP Best Practices In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive bus
macOS development environment setup: Setting up a new developer machine can be an ad-hoc, manual, and time-consuming process.
dev-setup Motivation Setting up a new developer machine can be an ad-hoc, manual, and time-consuming process. dev-setup aims to simplify the process w
Machine Learning University: Accelerated Natural Language Processing Class
Machine Learning University: Accelerated Natural Language Processing Class This repository contains slides, notebooks and datasets for the Machine Lea
Code and data accompanying Natural Language Processing with PyTorch
Natural Language Processing with PyTorch Build Intelligent Language Applications Using Deep Learning By Delip Rao and Brian McMahan Welcome. This is a
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 Tensorflow 2.0
NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab
🙄 Difficult algorithm, Simple code.
🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin
Pure python implementations of popular ML algorithms.
Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks
Housing Price Prediction Using Machine Learning.
HOUSING PRICE PREDICTION USING MACHINE LEARNING DESCRIPTION Housing Price Prediction Using Machine Learning is to predict the data of housings. Here I
Research into Forex price prediction from price history using Deep Sequence Modeling with Stacked LSTMs.
Forex Data Prediction via Recurrent Neural Network Deep Sequence Modeling Research Paper Our research paper can be viewed here Installation Clone the
python driver for fingerprint machine (ZKTeco biometrics)
fpmachine python driver for fingerprint machine (ZKTeco biometrics) support until now 2 model supported and tested ZMM100_TFT and ZMM220_TFT install p
To attract customers, the hotel chain has added to its website the ability to book a room without prepayment
To attract customers, the hotel chain has added to its website the ability to book a room without prepayment. We need to predict whether the customer is going to reject the booking or not. Since in case of refusal, the hotel incurs losses.
Using machine learning to predict undergrad college admissions.
College-Prediction Project- Overview: Many have tried, many have failed. Few trailblazers are ambitious enought to chase acceptance into the top 15 un
Neural-net-from-scratch - A simple Neural Network from scratch in Python using the Pymathrix library
A Simple Neural Network from scratch A Simple Neural Network from scratch in Pyt
Machine Learning for Time-Series with Python.Published by Packt
Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am
The Wearables Development Toolkit - a development environment for activity recognition applications with sensor signals
Wearables Development Toolkit (WDK) The Wearables Development Toolkit (WDK) is a framework and set of tools to facilitate the iterative development of
DeltaPy - Tabular Data Augmentation (by @firmai)
DeltaPy — Tabular Data Augmentation & Feature Engineering Finance Quant Machine Learning ML-Quant.com - Automated Research Repository Introduction T
Library for time-series-forecasting-as-a-service.
TIMEX TIMEX (referred in code as timexseries) is a framework for time-series-forecasting-as-a-service. Its main goal is to provide a simple and generi
Automated Time Series Forecasting
AutoTS AutoTS is a time series package for Python designed for rapidly deploying high-accuracy forecasts at scale. There are dozens of forecasting mod
Machine Learning Time-Series Platform
cesium: Open-Source Platform for Time Series Inference Summary cesium is an open source library that allows users to: extract features from raw time s
An API-first distributed deployment system of deep learning models using timeseries data to analyze and predict systems behaviour
Gordo Building thousands of models with timeseries data to monitor systems. Table of content About Examples Install Uninstall Developer manual How to
(JMLR' 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin
Forecast dynamically at scale with this unique package. pip install scalecast
🌄 Scalecast: Dynamic Forecasting at Scale About This package uses a scaleable forecasting approach in Python with common scikit-learn and statsmodels
Hierarchical Time Series Forecasting with a familiar API
scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work
An open source python library for automated feature engineering
"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to
WTTE-RNN a framework for churn and time to event prediction
WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p
Code to accompany our paper "Continual Learning Through Synaptic Intelligence" ICML 2017
Continual Learning Through Synaptic Intelligence This repository contains code to reproduce the key findings of our path integral approach to prevent
A PyTorch implementation of the continual learning experiments with deep neural networks
Brain-Inspired Replay A PyTorch implementation of the continual learning experiments with deep neural networks described in the following paper: Brain
Software Engineer Salary Prediction
Based on 2021 stack overflow data, this machine learning web application helps one predict the salary based on years of experience, level of education and the country they work in.
Medical appointments No-Show classifier
Medical Appointments No-shows Why do 20% of patients miss their scheduled appointments? A person makes a doctor appointment, receives all the instruct
Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máquina.
Estatistica para Ciência de Dados e Machine Learning Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máqui
Experiments for Operating Systems Lab (ETCS-352)
Operating Systems Lab (ETCS-352) Experiments for Operating Systems Lab (ETCS-352) performed by me in 2021 at uni. All codes are written by me except t
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
Repository of continual learning papers
Continual learning paper repository This repository contains an incomplete (but dynamically updated) list of papers exploring continual learning in ma
A curated list of the top 10 computer vision papers in 2021 with video demos, articles, code and paper reference.
The Top 10 Computer Vision Papers of 2021 The top 10 computer vision papers in 2021 with video demos, articles, code, and paper reference. While the w
Covid-polygraph - a set of Machine Learning-driven fact-checking tools
Covid-polygraph, a set of Machine Learning-driven fact-checking tools that aim to address the issue of misleading information related to COVID-19.
Tutorial on scikit-learn and IPython for parallel machine learning
Parallel Machine Learning with scikit-learn and IPython Video recording of this tutorial given at PyCon in 2013. The tutorial material has been rearra
Datasets, tools, and benchmarks for representation learning of code.
The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided
General Assembly's 2015 Data Science course in Washington, DC
DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (
Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques
Data Science 45-min Intros Every week*, our data science team @Gnip (aka @TwitterBoulder) gets together for about 50 minutes to learn something. While
🔅 Shapash makes Machine Learning models transparent and understandable by everyone
🎉 What's new ? Version New Feature Description Tutorial 1.6.x Explainability Quality Metrics To help increase confidence in explainability methods, y
Creative Applications of Deep Learning w/ Tensorflow
Creative Applications of Deep Learning w/ Tensorflow This repository contains lecture transcripts and homework assignments as Jupyter Notebooks for th
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
Here are the sections: Data Science Cheatsheets Data Science EBooks Data Science Question Bank Data Science Case Studies Data Science Portfolio Data J
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
Spark Python Notebooks This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, fro
🤖 ⚡ scikit-learn tips
🤖 ⚡ scikit-learn tips New tips are posted on LinkedIn, Twitter, and Facebook. 👉 Sign up to receive 2 video tips by email every week! 👈 List of all
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Hands-on-Machine-Learning 目的 这份笔记旨在帮助中文学习者以一种较快较系统的方式入门机器学习, 是在学习Hands-on Machine Learning with Scikit-Learn and TensorFlow这本书的 时候做的个人笔记: 此项目的可取之处 原书的
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
HackerMath for Machine Learning “Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.” ― Richard
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.
Koç University deep learning framework.
Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU
Hide screen when boss is approaching.
BossSensor Hide your screen when your boss is approaching. Demo The boss stands up. He is approaching. When he is approaching, the program fetches fac
Mycroft Core, the Mycroft Artificial Intelligence platform.
Mycroft Mycroft is a hackable open source voice assistant. Table of Contents Getting Started Running Mycroft Using Mycroft Home Device and Account Man
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection Learning Resources Outlier Detection (also known as Anomaly Detection) is an exciting yet challenging field, which aims to identify
Largest list of models for Core ML (for iOS 11+)
Since iOS 11, Apple released Core ML framework to help developers integrate machine learning models into applications. The official documentation We'v
A list of NLP(Natural Language Processing) tutorials
NLP Tutorial A list of NLP(Natural Language Processing) tutorials built on PyTorch. Table of Contents A step-by-step tutorial on how to implement and
My solution to the book A Collection of Data Science Take-Home Challenges
DS-Take-Home Solution to the book "A Collection of Data Science Take-Home Challenges". Note: Please don't contact me for the dataset. This repository
This Artificial Intelligence program can take a black and white/grayscale image and generate a realistic or plausible colorized version of the same picture.
Colorizer The point of this project is to write a program capable of taking a black and white / grayscale image, and generating a realistic or plausib
A curated list of awesome Active Learning
Awesome Active Learning 🤩 A curated list of awesome Active Learning ! 🤩 Background (image source: Settles, Burr) What is Active Learning? Active lea
python 93% acc. CNN Dogs Vs Cats ( Pytorch )
English | 简体中文(测试中...敬请期待) Cnn-Classification-Dog-Vs-Cat 猫狗辨别 (pytorch版本) CNN Resnet18 的猫狗分类器,基于ResNet及其变体网路系列,对于一般的图像识别任务表现优异,模型精准度高达93%(小型样本)。 项目制作于
Python bindings for Basler's VisualApplets TCL script generation
About visualapplets.py The Basler AG company provides a TCL scripting engine to automatize the creation of VisualApplets designs (a former Silicon Sof
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
MNE-Python MNE-Python software is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, E
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J
Python Client for Algorithmia Algorithms and Data API
Algorithmia Common Library (python) Python client library for accessing the Algorithmia API For API documentation, see the PythonDocs Algorithm Develo
A Python Package For System Identification Using NARMAX Models
SysIdentPy is a Python module for System Identification using NARMAX models built on top of numpy and is distributed under the 3-Clause BSD license. N
SnailJumper - A game that is developed as an assignment for Computer Intelligence course
Snail jumper Neuroevolution game assignment. Fall 2021 - Computer Intelligence.
Machine Learning Study 혼자 해보기
Machine Learning Study 혼자 해보기 기여자 (Contributors) ✨ Teddy Lee 🏠 HongJaeKwon 🏠 Seungwoo Han 🏠 Tae Heon Kim 🏠 Steve Kwon 🏠 SW Song 🏠 K1A2 🏠 Wooil
Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
feature-engineering-book This repo accompanies "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari. O'Reilly, 2018. The repo
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
Machine Learning in Asset Management (by @firmai)
Machine Learning in Asset Management If you like this type of content then visit ML Quant site below: https://www.ml-quant.com/ Part One Follow this l
Machine Learning University: Accelerated Computer Vision Class
Machine Learning University: Accelerated Computer Vision Class This repository contains slides, notebooks, and datasets for the Machine Learning Unive
Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras
Face Mask Detection Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet
One Pixel Attack How simple is it to cause a deep neural network to misclassify an image if an attacker is only allowed to modify the color of one pix
Vehicle detection using machine learning and computer vision techniques for Udacity's Self-Driving Car Engineer Nanodegree.
Vehicle Detection Video demo Overview Vehicle detection using these machine learning and computer vision techniques. Linear SVM HOG(Histogram of Orien
Implementations of CNNs, RNNs, GANs, etc
Tensorflow Programs and Tutorials This repository will contain Tensorflow tutorials on a lot of the most popular deep learning concepts. It'll also co
A general-purpose encoder-decoder framework for Tensorflow
READ THE DOCUMENTATION CONTRIBUTING A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summariz
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales. In this case, we ended up using XGBoost because it was the one with a higher score and less overfitting.
An AI made using artificial intelligence (AI) and machine learning algorithms (ML) .
DTech.AIML An AI made using artificial intelligence (AI) and machine learning algorithms (ML) . This is created by help of some members in my team and
Crunchdao - Python API for the Crunchdao machine learning tournament
Python API for the Crunchdao machine learning tournament Interact with the Crunc
Its a Plant Leaf Disease Detection System based on Machine Learning.
My_Project_Code Its a Plant Leaf Disease Detection System based on Machine Learning. I have used Tomato Leaves Dataset from kaggle. This system detect
Coinloggr - A learning resource and social platform for the coin collecting community
Coinloggr A learning resource and social platform for the coin collecting commun
Multi-Modal Machine Learning toolkit based on PaddlePaddle.
简体中文 | English PaddleMM 简介 飞桨多模态学习工具包 PaddleMM 旨在于提供模态联合学习和跨模态学习算法模型库,为处理图片文本等多模态数据提供高效的解决方案,助力多模态学习应用落地。 近期更新 2022.1.5 发布 PaddleMM 初始版本 v1.0 特性 丰富的任务
🚀 An end-to-end ML applications using PyTorch, W&B, FastAPI, Docker, Streamlit and Heroku
🚀 An end-to-end ML applications using PyTorch, W&B, FastAPI, Docker, Streamlit and Heroku
Reinforcement learning algorithms in RLlib
raylab Reinforcement learning algorithms in RLlib and PyTorch. Installation pip install raylab Quickstart Raylab provides agents and environments to b