AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
- Updated
Nov 12, 2024 - Python
AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Open standard for machine learning interoperability
Open Machine Learning Course
A unified framework for machine learning with time series
Fast and Accurate ML in 3 Lines of Code
Automated Machine Learning with scikit-learn
An open source python library for automated feature engineering
Flower: A Friendly Federated AI Framework
🍊 📊 💡 Orange: Interactive data analysis
Visual analysis and diagnostic tools to facilitate machine learning model selection.
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
Seamlessly integrate LLMs into scikit-learn.
Hummingbird compiles trained ML models into tensor computation for faster inference.
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
a delightful machine learning tool that allows you to train, test, and use models without writing code
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
High-Performance Symbolic Regression in Python and Julia
Sequential model-based optimization with a `scipy.optimize` interface
Created by David Cournapeau
Released January 05, 2010
Latest release 7 days ago