Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
A resuable template for Machine Learning projects
C++ image processing and machine learning library with using of SIMD: SSE, AVX, AVX-512, AMX for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM.
This Repository consists of programs related to AI-ML-DL-NLP-CV. Few examples include - KNN, Naive Bayes, Decision Trees, EDA etc.
📖 Parses and validates valohai.yaml files.
⚡ Cloud-native, AI-powered, document processing pipelines on AWS.
Explain a black-box module in natural language.
Applied category theory library in several languages
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
An open source copy of my comprehensive full stack progressive web app focused on machine learning, media, and marketing.
Streamlit — A faster way to build and share data apps.
machine learning theory and exercises
Tensors and Dynamic neural networks in Python with strong GPU acceleration
The open-source observability platform everyone needs!
AI + Data, online. https://vespa.ai
Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, with more integrations coming..
Web application for predicting the number of available bike stands at one of the MBajk bike stations.
GitHub Pages and VScode to create a custom html website and host my data analytics projects portfolio - 2024
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.