Python Learning-with-limited-labeled-data Resources

Equipped customers with insights about their EVs Hourly energy consumption and helped predict future charging behavior using LSTM model. Designed sample dashboard with insights and recommendation for customers.

Project IBEX A Celery application to collect data, download media and extract information from social media APIs. Requirements You must have a Redis D

Processing-data-with-python This is a simple example showing how to use Pandas to create a dataframe and the processing data with python. The jupyter

Machine-Learning with python (jupyter) 머신러닝 야학 작심 10일과 쥬피터 노트북 기반 데이터 사이언스 시작 들어가기전 https://nbviewer.org/ 페이지를 통해서 쥬피터 노트북 내용을 볼 수 있다. 위 페이지에서 현재 레포 기

Nobel_Data_Analysis This project is for analyzing a set of data about people who have won the Nobel Prize in different fields and different countries

Investigating EV charging data Introduction: Got an opportunity to work with a home monitoring technology company over the last 6 months whose goal wa

Gravitational-Wave-Analysis This project showcases how to analyze the Gravitational wave data stored at LIGO/VIRGO observatories, using Python program

Slido-Automated-VoteBot This python script allows you to manipulate the audience data from Sl.ido surveys Since Slido blocks interference from automat

Laporan Proyek Machine Learning - Azhar Rizki Zulma Project Overview Domain proyek yang dipilih dalam proyek machine learning ini adalah mengenai hibu

A simple code to process images using contrast limited adaptive histogram equalization. Image processing is becoming a major part of data processig.

The Cormen-lib module is an insular data structures and algorithms library based on the Thomas H. Cormen's Introduction to Algorithms Third Edition. This library was made specifically for administering and grading assignments related to data structure and algorithms in computer science.

Collapse by Conditioning: Training Class-conditional GANs with Limited Data Moha

DTCN This is the implementation of our paper "Sequential Prediction of Social Me

ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

Video-Captioning - A machine Learning project to generate captions for video frames indicating the relationship between the objects in the video

Personal Finance Forecaster - An AI tool for forecasting personal expenses

GoogleFormSpammer - A simple CLI script to spam Google Forms used by Crypto Wallet scammers to collect stolen data

Task Overview | Installation Instructions | Link to Module 2 Introduction Experience Technology at JP Morgan Chase Try out what real work is like in t

PostQF Copyright © 2022 Ralph Seichter PostQF is a user-friendly Postfix queue data filter which operates on data produced by postqueue -j. See the ma

Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are statistical models that allow these properties to be simulated (Joe 2014). As such, copula generated data have shown potential to improve the generalization of machine learning (ML) emulators (Meyer et al. 2021) or anonymize real-data datasets (Patki et al. 2016).

A feature store is a data storage system for data science and machine-learning. It can store raw data and also transformed features, which can be fed straight into an ML model or training script.

package tests docs license stats support This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML

Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API.

Data visualisation Hey, You can learn Basic to advanced level Data visualisation techniques from this Repository. Data visualization is the graphic re

ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference, with the design goal of unifying the automation (of Monte Carlo simulations), user-friendliness (of the library), accessibility (from multiple programming environments), high-performance (at runtime), and scalability (across many parallel processors).

Create charts with Python in a very similar way to creating charts using Chart.js. The charts created are fully configurable, interactive and modular and are displayed directly in the output of the the cells of your jupyter notebook environment.

visualize_ML visualize_ML is a python package made to visualize some of the steps involved while dealing with a Machine Learning problem. It is build

real-life-contra Description A python script that translates the body movement into in game control. Welcome to all new real life contra a deep learni

Equibles Stocks API for Python Requirements. Python 2.7 and 3.4+ Installation & Usage pip install If the python package is hosted on Github, you can i

Author Ayanwoye, Gideon Ayandele - [email protected] SOLUTION TO HAMOYE STAGE A QUIZ INTRODUCTION TO PYTHON FOR MACHINE LEARNING The dataset is prov

HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This

Agar.io_Q-Learning_AI An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available act

ccserver A server and client for passing data between computercraft computers/turtles across dimensions or even servers. pastebin get zUnE5N0v client

Feature engineering and machine learning: together at last! Lambdo is a workflow engine which significantly simplifies data analysis by unifying featu

INFO-H515 - Big Data Scalable Analytics Jacopo De Stefani, Giovanni Buroni, Théo Verhelst and Gianluca Bontempi - Machine Learning Group Exercise clas

VarDACAE This module is used to create Convolutional AutoEncoders for Variational Data Assimilation. A user can define, create and train an AE for Dat

Support Vector Machine (SVM) Explorer This app has been moved here. This repo is likely outdated and will not be updated. This is a learning tool and

**Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining.** S

About scikit-learn is a python module for machine learning built on top of numpy / scipy. The purpose of the scikit-learn-tutorial subproject is to le

Sentiment Analyzer The goal of this project is to perform sentiment analysis on textual data that people generally post on websites like social networ

Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers

neon_course This repository contains several jupyter notebooks to help users learn to use neon, our deep learning framework. For more information, see

climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works

Dive into Machine Learning Hi there! You might find this guide helpful if: You know Python or you're learning it 🐍 You're new to Machine Learning You

TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow (Google's Deep Learning framework) with breakpoints + real-time visualization of the data flowing through the computational graph.

Suiron Machine Learning for RC Cars Prediction visualization (green = actual, blue = prediction) Click the video below to see it in action! Dependenci

Python for Data Analysis, 2nd Edition Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media Buy

This repository contains Jupyter notebooks implementing the algorithms found in the book and summary of the textbook.

Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm

TDA INF421(Conception et analyse d'algorithmes) Projet : Topological Data Analysis SphereMin Etant donné un nuage des points, ce programme contient de

Data Scientist Learning Plan Demonstrate the breadth and depth of your data science skills by earning all of the Databricks Data Scientist credentials

sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ

Home Credit Default Risk: Open Solution This is an open solution to the Home Credit Default Risk challenge 🏡 . More competitions 🎇 Check collection

Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently This repository is the official implementat

Google AI Open Images - Object Detection Track: Open Solution This is an open solution to the Google AI Open Images - Object Detection Track 😃 More c

TGS Salt Identification Challenge This is an open solution to the TGS Salt Identification Challenge. Note Unfortunately, we can no longer provide supp

Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t

This is a project for analysis and estimation of House Prices in King County USA The .csv file contains the data of the house and the .ipynb file con

Self-Supervised Anomaly Segmentation Intorduction This is a PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmen

Python-Sreamlit-Duplicate-Records-Finder-Remover Streamlit is an open-source Python library that makes it easy to create and share beautiful, custom w

A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches

NBA MVP Predictor A machine learning model using RandomForest Regression that predicts NBA MVP's using player data. Explore the docs » View Demo · Rep

Simple Translator in Python Project Description: In this project, we'll be making a very simple translator in Python using some libraries. Requirement

Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a

Symbolic Learning to Optimize This is the official implementation for ICLR-2022 paper "Symbolic Learning to Optimize: Towards Interpretability and Sca

Starter code: Kaggle Toxic Comment Classification Challenge More competitions 🎇 Check collection of public projects 🎁 , where you can find multiple

Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents [Project Page] [Paper] [Video] Wenlong Huang1, Pieter Abbee

Reinforcement Learning in Finance quats@dev Webinar This repository provides the code for the free quants@dev Webinar series about Reinforcement Learn

Computational Optimal Transport for Machine Learning Reading Group Over the last few years, optimal transport (OT) has quickly become a central topic

dbd: database prototyping tool dbd is a database prototyping tool that enables data analysts and engineers to quickly load and transform data in SQL d

COMS20011_2021 Data-driven Computer Science UoB Staff Laurence Aitchison [[email protected]] (unit director) Majid Mirmehdi [m.mirmehdi

Deep learning Udacity Course Deep Learning Topics with Computer Vision & NLP for the AWS Machine Learning Engineer Nanodegree Program Tasks are mostly

RedliningExploration The Google Colaboratory file contained in this repository contains work inspired by a project on educational inequality in the Ph

An interactive App to play with Spotify data, both from the Spotify Web API and from CSV datasets.

Deep Learning for Morphological Profiling An end-to-end implementation of a ML System for morphological profiling using self-supervised learning to di

Osborne Mine, Australia - Airborne total-field magnetic anomaly This is a section of a survey acquired in 1990 by the Queensland Government, Australia

Credit Card Fraud Detection Introduction Online transactions have become a crucial part of any business over the years. Many of those transactions use

Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning My

Fast Forward Computer Vision: train models at a fraction of the cost with accele

Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int

The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.

Decision-Threshold-ML Tutorial for improve skills: 'Decision Threshold In Machine Learning' (from GeeksforGeeks) by Marcus Mariano For more informatio

Binary Classification Problem with Machine Learning Solving Approach: 1) Ultimate Goal of the Assignment: This assignment is about solving a binary cl

ServiceX_Uproot_Transformer ServiceX Transformer that converts flat ROOT ntuples into columnwise data Usage You can invoke the transformer from the co

Overview Welcome to the Step-X repository. This repo is dedicated to the data extraction and manipulation of the World Bank's database called STEP. Be

GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.

Transformer-in-Vision Recent Transformer-based CV and related works. Welcome to comment/contribute! Keep updated. Resource SCENIC: A JAX Library for C

PyTracking A general python framework for visual object tracking and video object segmentation, based on PyTorch. 📣 Two tracking/VOS papers accepted

Learning to Prompt for Continual Learning (L2P) Official Jax Implementation L2P is a novel continual learning technique which learns to dynamically pr

TransZero++ This repository contains the testing code for the paper "TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning" submitted

DI-treetensor treetensor is a generalized tree-based tensor structure mainly developed by OpenDILab Contributors. Almost all the operation can be supp

FSL-Mate is a collection of resources for few-shot learning (FSL). In particular, FSL-Mate currently contains FewShotPapers: a paper list which tracks

ECLARE ECLARE: Extreme Classification with Label Graph Correlations @InProceedings{Mittal21b, author = "Mittal, A. and Sachdeva, N. and Agrawal

GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,

Prompt Tuning This is the code to reproduce the experiments from the EMNLP 2021 paper "The Power of Scale for Parameter-Efficient Prompt Tuning" (Lest

Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark Project | Arxiv | YouTube | | Abstract In recent years, deep learning-based methods

LEAP: Learning Articulated Occupancy of People Paper | Video | Project Page This is the official implementation of the CVPR 2021 submission LEAP: Lear

NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise

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