leigaoxing

leigaoxing's Stars

• f/awesome-chatgpt-prompts

  This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.

  Language:JavaScript122k1.5k016.4k

• tesseract-ocr/tesseract

  Tesseract Open Source OCR Engine (main repository)

  Language:C++65.5k1.7k2.7k9.8k

• k88hudson/git-flight-rules

  Flight rules for git

  42k652733.2k

• RSSNext/Follow

  🧡 Follow everything in one place

  Language:TypeScript23.3k911.7k980

• blackmatrix7/ios_rule_script

  分流规则、重写写规则及脚本。

  Language:JavaScript20.4k2611.2k3.3k

• Johnshall/Shadowrocket-ADBlock-Rules-Forever

  提供多款 Shadowrocket 规则，拥有强劲的广告过滤功能。每日 8 时重新构建规则。

  14.5k80331915

• phiresky/ripgrep-all

  rga: ripgrep, but also search in PDFs, E-Books, Office documents, zip, tar.gz, etc.

  Language:Rust8.6k43196185

• myhhub/stock

  stock股票.获取股票数据,计算股票指标,筹码分布,识别股票形态,综合选股,选股策略,股票验证回测,股票自动交易,支持PC及移动设备。

  Language:Python7.9k1262121.6k

• JerBouma/FinanceDatabase

  This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.

  Language:Jupyter Notebook4.5k9541497

• riscv-collab/riscv-gnu-toolchain

  GNU toolchain for RISC-V, including GCC

  Language:C3.8k1451.2k1.2k

• app2smile/rules

  iOS App去广告

  Language:JavaScript3.6k31206231

• achristmascarl/rainfrog

  🐸 a database management tui for postgres

  Language:Rust3.5k194665

• JerBouma/FinanceToolkit

  Transparent and Efficient Financial Analysis

  Language:Python3.3k7094386

• yaolifeng0629/Awesome-independent-tools

  独立开发者出海工具收集站（Awesome Independent developer sea tool collection station）

  1.8k152138

• DemonDamon/FinnewsHunter

  从新浪财经、每经网、金融界、**证券网、证券时报网上，爬取上市公司（个股）的历史新闻文本数据进行文本分析、提取特征集，然后利用SVM、随机森林等分类器进行训练，最后对实施抓取的新闻数据进行分类预测

  Language:Python1.1k318281

• gcui-art/album-ai

  AI-First Album: Chat with your gallery using plain language! LLM Vision + RAG + Album/Gallery.

  Language:TypeScript76017566

• lucasmrdt/TheBigPromptLibrary

  A collection of prompts, system prompts and LLM instructions

  Language:HTML5664065

• soberhacker/obsidian-telegram-sync

  Transfer messages and files from Telegram to Obsidian

  Language:TypeScript418710937

• pskun/finance_news_analysis

  金融新闻数据挖掘分析

  Language:C++326236127

• GallenQiu/FinanceReportAnalysis

  获取3775家上市公司近5年财务报表，建立财务报表分析模型，借助pyqt生成窗口化展示页面。

  Language:Python21381114

• RealKai42/llm-course-basic

  大模型的基础入门课配套代码

  Language:JavaScript1583013

• neocl/jamdict

  Python 3 library for manipulating Jim Breen's JMdict, KanjiDic2, JMnedict and kanji-radical mappings

  Language:Python13742413

• MartinLwx/dotfiles

  Language:Lua904123

• xiaopeng163/learn-k8s-from-scratch

  Language:Shell6241941

• iiiBird/obsidian-telegram-reminder

  Obsidian Telegram Reminder Plugin

  Language:TypeScript32555

• yogkin/Programming-Notes

  Programming Notes

  302014

• hgnx/binance-position-tracking-bot

  Enabling real-time monitoring and analysis of Binance Futures trader's activities, complimented with Telegram notifications.

  Language:Python272315

• ja-netfilter2/pandora

  Language:Python262123

• Ashishsinha10/stock-market-analysis-using-python-numpy-pandas

  The aim of the project was to extract information about various technology stocks mainly - Google, Apple, Microsoft and Amazon from the online stock trading sites - Yahoo Finance and to visualize different aspects of the stocks like the Adjusted Closing Prices, Volumes of stocks traded on a particular day, moving averages of the closing price-to get a basic idea of which way the price is moving by cutting down noise from the data and the daily returns on the stocks. Correlation plots were created for the daily percentage return and Closing prices of the stocks to check how correlated two stocks are. It was obvious that all technology stocks are positively correlated but few like Amazon and Microsoft were highly correlated with each other. The information gathered on daily percentage returns was further used for Risk Analysis by calculating the Expected Return (Average / mean return of the stock) and standard deviation (measurement of Risk -> Greater the std. dev. greater is the risk and vice versa). A scatter plot was created for comparing the Expected return of stocks to its risk. This helped in visualizing the risk factor of various stocks (stocks with high standard deviation and low return).

  Language:Jupyter Notebook21107

• ilitzkyd/Stock-Market-Analysis

  This Python script provides two main functionalities: stock and economic indicators analysis. It utilizes the Yahoo Finance to fetch historical stock price data for multiple tickers and the fredapi library to fetch economic indicator data from the FRED API.

  Language:Jupyter Notebook16112