Step by step explanation/tutorial of llama2.c

深度学习经典、新论文逐段精读

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

In this repository, an event-driven backtester is implemented based on QuantStart articles. The backtester is programmed in Python featuring numerous improvements, in terms of coding structure, dat…

A list of awesome compiler projects and papers for tensor computation and deep learning.

Visualizer for neural network, deep learning and machine learning models

Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

This MLOps project productionizes a Deep Reinforcement Learning agent with a scalable, distributed data streaming infrastructure using Kafka and Ray. A thorough walkthrough of the code is described…

Python Stream Processing

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 Advers…

Streaming Value At Risk

NumPy aware dynamic Python compiler using LLVM

In this repository, I have developed the entire server-side principal architecture for real-time stock market prediction with Machine Learning. I have used Tensorflow.js for constructing ml model a…

Python Algorithmic Trading Library

Low-latency algorithmic trading platform written in Rust

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Numba, cuDF, and Dask.

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

High-performance TensorFlow library for quantitative finance.

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

Asynchronous event I/O driven quantitative trading framework.

AI量化实验室，专注将前沿人工智能技术(深度学习/强化学习/知识图谱)应用于金融量化投资。

QTPyLib, Pythonic Algorithmic Trading

Asynchronous event I/O driven quantitative trading framework.

Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.

🔎 📈 🐍 💰 Backtest trading strategies in Python.

Code for Machine Learning for Algorithmic Trading, 2nd edition.