jenizar

jenizar's Stars

• hamukazu/primedayapp

  This app calculates prime number days.

  Language:HTML23

• yhangf/wechat

  :lemon:Use Flask for web WeChat.

  Language:JavaScript52

• gxercavins/image-api

  Image Processing API using Python + Flask + PIL

  Language:Python7622

• leemengtw/cat-recognition-app

  The repository include code for build a ML application using Flask, Tensorflow

  Language:Jupyter Notebook2113

• yinguobing/cnn-facial-landmark

  Training code for facial landmark detection based on deep convolutional neural network.

  Language:Python631180

• caoshiyi/Simple_Dashboard

  Flask + D3: A simple dashboard with Choropleth Map, Radar Chart and Bar Chart.

  Language:HTML31

• shengqiangzhang/examples-of-web-crawlers

  一些非常有趣的python爬虫例子,对新手比较友好,主要爬取淘宝、天猫、微信、微信读书、豆瓣、QQ等网站。(Some interesting examples of python crawlers that are friendly to beginners. )

  Language:Python14k3.8k

• victordibia/handtracking

  Building a Real-time Hand-Detector using Neural Networks (SSD) on Tensorflow

  Language:Python1.7k461

• jrosebr1/color_transfer

  Performs color transfer between two images. Loosely based on the "Color Transfer between Images" paper by Reinhard et al., 2001.

  Language:Python498148

• jrosebr1/simple-keras-rest-api

  A simple Keras REST API using Flask

  Language:Python375197

• knwng/awesome-vehicle-re-identification

  collection of dataset&paper&code on Vehicle Re-Identification

  41576

• mjhea0/docker-workshop

  Language:JavaScript711

• chenyuntc/simple-faster-rcnn-pytorch

  A simplified implemention of Faster R-CNN that replicate performance from origin paper

  Language:Jupyter Notebook4k1.1k

• imfing/keras-flask-deploy-webapp

  :smiley_cat: Pretty & simple image classifier app template. Deploy your own trained model or pre-trained model (VGG, ResNet, Densenet) to a web app using Flask in 10 minutes.

  Language:JavaScript1.2k469

• PySimpleGUI/PySimpleGUI

  Python GUIs for Humans! PySimpleGUI is the top-rated Python application development environment. Launched in 2018 and actively developed, maintained, and supported in 2024. Transforms tkinter, Qt, WxPython, and Remi into a simple, intuitive, and fun experience for both hobbyists and expert users.

  Language:Python13.5k1.8k

• dushan14/books-store

  A Simple Web application to use flask python web framework.

  Language:Python2721

• chaitjo/regression-stock-prediction

  Predicting Google’s stock price using regression

  Language:Python6044

• python-visualization/folium

  Python Data. Leaflet.js Maps.

  Language:Python7k2.2k

• mahmoud/awesome-python-applications

  💿 Free software that works great, and also happens to be open-source Python.

  Language:Jupyter Notebook16.9k2.7k

• OpenGeoscience/geonotebook

  A Jupyter notebook extension for geospatial visualization and analysis

  Language:Python1.1k142

• NicholasTanWeiHong/dash-stock-visualizations

  Dash Application for Stock Charting and Technical Analysis

  Language:Python82

• YoongiKim/AutoCrawler

  Google, Naver multiprocess image web crawler (Selenium)

  Language:Python1.6k420

• ucg8j/awesome-dash

  A curated list of awesome Dash (plotly) resources

  Language:Python2.1k260

• plotly/dash-stock-tickers-demo-app

  Dash Demo App - Stock Tickers

  Language:CSS13392

• TrainingByPackt/Data-Visualization-with-Python-eLearning

  Create an impact with meaningful data insights using interactive and engaging visuals

  Language:Jupyter Notebook44

• TrainingByPackt/Data-Science-for-Marketing-Analytics

  Achieve your marketing goals with the data analytics power of Python

  Language:Jupyter Notebook212130

• NVIDIA/FastPhotoStyle

  Style transfer, deep learning, feature transform

  Language:Python11.2k1.2k

• lexfridman/mit-deep-learning

  Tutorials, assignments, and competitions for MIT Deep Learning related courses.

  Language:Jupyter Notebook10.2k2.2k

• borisbanushev/stockpredictionai

  In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

  4.4k1.7k

• madhavi-r/Interactive-Dashboard

  An app deployed on Heroku that visualizes a sample data from Sqlite using Plotly and Flask.

  Language:JavaScript2