Machine-Learning-Algorithms-Tutorials

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.

deep learning for image processing including classification and object-detection etc.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

深度学习入门教程, 优秀文章, Deep Learning Tutorial

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

An open-source, low-code machine learning library in Python

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

All-in-One Development Tool based on PaddlePaddle（飞桨低代码开发工具）