trekhleb / homemade-machine-learning

#学习与技能提升#本仓库包含了多种基于 JavaScript 的算法与数据结构

#学习与技能提升#📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.

#计算机科学#🤖 NanoNeuron is 7 simple JavaScript functions that will give you a feeling of how machines can actually "learn"

机器学习相关的框架、库、软件精选

#计算机科学#A complete daily plan for studying to become a machine learning engineer.

#计算机科学#Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learnin...

《Python 数据科学手册》，全文以Jupyter Notebooks形式呈现

#Awesome#machine learning and deep learning tutorials, articles and other resources

Basic Machine Learning and Deep Learning

#自然语言处理#A collection of machine learning examples and tutorials.

#计算机科学#Azure 机器学习Python SDK notebooks 示例

#计算机科学#Keras是一个基于 Python 的深度学习库，能够在TensorFlow、Microsoft Cognitive Toolkit、Theano或PlaidML之上运行。

机器学习算法python实现

#大语言模型#微软生成式AI课程，12课时

#计算机科学#深度学习论文

#面试#该仓库包含了 Python 实现的各种算法，用于学习目的。

Content for Udacity's Machine Learning curriculum

#Awesome#A curated list of awesome Deep Learning tutorials, projects and communities.

#自然语言处理#深度学习示例

#计算机科学#Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

#计算机科学#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 2018.0...

#计算机科学#Python 数据科学学习笔记：深度学习 (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, 大数据 (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python 核心, AWS, Linux命令

Deep Learning Tutorial notes and code. See the wiki for more info.