speech-recognition-transfer-learning

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.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

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

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

Open Machine Learning Course

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

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.

? Collection of Kaggle Solutions and Ideas ?

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.