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Lics's Projects

awesome-automl-papers icon awesome-automl-papers

A curated list of automated machine learning papers, articles, tutorials, slides and projects

awesome-pytorch-list icon awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

ax icon ax

Adaptive Experimentation Platform

catboost icon catboost

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.

d2l-pytorch icon d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

data-science-ipython-notebooks icon data-science-ipython-notebooks

Recently updated with 50 new notebooks! 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.

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,近30万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06

dive-into-dl-pytorch icon dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet代码实现改为PyTorch实现。

featuretools icon featuretools

An open source python framework for automated feature engineering

hello-algo icon hello-algo

《Hello 算法》是一本动画图解、能运行、可提问的数据结构与算法入门书,支持 Java, C++, Python, Go, JS, TS, C#, Swift, Zig 等语言。

hyperopt icon hyperopt

Distributed Asynchronous Hyperparameter Optimization in Python

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