MAYUYUY's starred repositories
v2ray
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free-programming-books
:books: Freely available programming books
fucking-algorithm
刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.
cracking-the-data-science-interview
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
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,50余万字。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scutjy2015@163.com 版权所有,违权必究 Tan 2018.06
chatgpt-prompts-for-academic-writing
This list of writing prompts covers a range of topics and tasks, including brainstorming research ideas, improving language and style, conducting literature reviews, and developing research plans.
animating-resume
饥人谷出品:一个会动的简历。欢迎 Fork ➡️
CS-Books-PDF
Computer Science Books 计算机专业相关书籍 PDF
python-docs-samples
Code samples used on cloud.google.com
transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
pytorch-widedeep
A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
tab-transformer-pytorch
Implementation of TabTransformer, attention network for tabular data, in Pytorch
transferlearning-tutorial
《迁移学习简明手册》LaTex源码
TransmogrifAI
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning
auto-sklearn
Automated Machine Learning with scikit-learn
Auto-PyTorch
Automatic architecture search and hyperparameter optimization for PyTorch
semi-supervised-pytorch
Implementations of various VAE-based semi-supervised and generative models in PyTorch
pytorch_tabular
A standard framework for modelling Deep Learning Models for tabular data
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
earthengine-community
Tutorials and content created by Earth Engine users, for Earth Engine users