Enrico's starred repositories
awesome-generative-ai-guide
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
rust-web-app
Code template for a production Web Application using Axum: The AwesomeApp Blueprint for Professional Web Development.
async-openai
Rust library for OpenAI
WebScraping_Linkedin
Connecting and Messaging Bot - Unlimited LinkedIn Connections and Messaging Abilities
linkedin_connect
Configurable and easy to use LinkedIn tool to automate connections with personalized messages.
go-backend-clean-architecture
A Go (Golang) Backend Clean Architecture project with Gin, MongoDB, JWT Authentication Middleware, Test, and Docker.
full-blockchain-solidity-course-js
Learn Blockchain, Solidity, and Full Stack Web3 Development with Javascript
zero-to-production
Code for "Zero To Production In Rust", a book on API development using Rust.
awesome-rust
A curated list of Rust code and resources.
Encoding-Word-Order-in-Complex-valued-Embedding
The code of Encoding Word Order in Complex-valued Embedding
Awesome-Transformer-Attention
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
Superalgos
Free, open-source crypto trading bot, automated bitcoin / cryptocurrency trading software, algorithmic trading bots. Visually design your crypto trading bot, leveraging an integrated charting system, data-mining, backtesting, paper trading, and multi-server crypto bot deployments.
binance-trade-bot
Automated cryptocurrency trading bot
amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
tensorflow
An Open Source Machine Learning Framework for Everyone
automl-streams
AutoML framework for implementing automated machine learning on data streams
Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall