Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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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.
Generate audiobooks from e-books, 50+ TTS engines with voice cloning and 1696 languages!
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.
- gbdt
- gbm
- machine-learning
- data-mining
TranslatedDeep Learning Tutorial, excellent articles
- deeplearning
- cnn
- rnn
- gan
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
- pytorch
- unet
- pytorch-unet
- semantic-segmentation
Open Machine Learning Course
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.
- machine-learning
- decision-trees
- gradient-boosting
- gbm
Kaggle Python docker image
MLBox is a powerful Automated Machine Learning python library.
- machine-learning
- auto-ml
- kaggle
- deep-learning
CatBoost tutorials repository
- catboost
- tutorials
- ipython-notebook
- ipython
Code for Kaggle EEG Detection competition