5921 Open source projects that are alternatives of or similar to Kaggle Environments

Implementation code for the paper "Generating Natural Language Adversarial Examples"

Placeholder for VTube Studio

Implemention of FCN-8 and FCN-16 with Keras and uses CRF as post processing

Open Sourced Curriculum and Lessons for an Introductory AI/ML Course

PyTorch implementation of SLAYER for training Spiking Neural Networks

A collection of Jupyter notebooks for learning Python from the ground up.

Almost Real-time Object Detection using Apple's CoreML and YOLO v1 -

Probability and Statistics Using Python Data Science Masters Course at UCSD (DSE 210)

Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.

Code for the Make Your Own Neural Network book

A Python package for heart rate variability analysis

Home assignments for data science positions

An application that provides personalized career and job search advice to jobseekers.

(한국어) 텍스트 마이닝을 위한 공부거리들

李航《统计学习方法》中机器学习模型的LaTeX公式笔记

A collection of Pyomo examples

Julia Project website

Multiscale Geographically Weighted Regression (MGWR)

All For NLP, especially Chinese.

Source code to accompany my paper "Poetic sound similarity vectors using phonetic features"

StarNet

Predict remaining useful life of a component based on historical sensor observations using automated feature engineering

BetterNetWork4SSD

🇰🇷PyTorch에서 제공하는 튜토리얼의 한국어 번역을 위한 저장소입니다. (Translate PyTorch tutorials in Korean🇰🇷)

Python for chemoinformatics

I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!

量子コンピュータ初学者のための自習教材

Time Series Forecasting Best Practices & Examples

This book serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data.

Fast Depth Densification for Occlusion-Aware Augmented Reality

Data Structures & Algorithms Nanodegree Program from Udacity

Training a Neural Network to Detect Gestures and Control Smart Home Devices with OpenCV in Python

Hands-on Tutorial on Automated Deep Learning

What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.

In computer science, a data structure is a data organization, management, and storage format that enables efficient access and modification. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data. (Using Python 3)

Pretrained Language Models for Korean

This is the code for "Sentiment Analysis - Data Lit #1" by Siraj Raval on Youtube

create sankey diagrams with matplotlib

Analyses about the COVID-19 virus

Files for Udemy Course on Algorithms and Data Structures

这个项目是基于论文YOLO9000: Better, Faster, Stronger的keras（backend：tensorflow）实现

Comparison tools

IPython widgets, interactive plots, interactive machine learning

Mish Deep Learning Activation Function for PyTorch / FastAI

Pop Music Maker built on HMM and Random Forest-like structure. Inspired by the desire to build my own model can serve as alternative to LSTMs / deep learning in generating pop music. Website is currently down due to costs incurred.

Referring Expression Datasets API

ICR - Automated and Intelligent Company Report Built in Python (by @firmai)

Programs for stock prediction and evaluation

Bayesian Analysis with Python by Packt

a bot that generates realistic replies using a combination of pretrained GPT-2 and BERT models

Deploy and scale serverless machine learning app - in 4 steps.

image processing codes to understand algorithm

This repository walks you through how to Build and Run YOLOv4 Object Detections with Darknet in the Cloud with Google Colab.

Enables the use of Stata together with Python via Jupyter (IPython) notebooks.

Examples of using Raster Vision on open datasets

Reading notes on the excellent "Designing Data-Intensive Applications"

Scientific analysis of nanoscale materials imaging data