#计算机科学#H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Me...
翻译 - 适用于更智能应用的开源快速可扩展机器学习平台:深度学习,梯度提升和XGBoost,随机森林,广义线性建模(逻辑回归,弹性网),K均值,PCA,堆叠集成,自动机器学习(AutoML)等。
#计算机科学#Practice and tutorial-style notebooks covering wide variety of machine learning techniques
#自然语言处理#General Assembly's 2015 Data Science course in Washington, DC
#自然语言处理#This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning...
#自然语言处理#Generating multiple choice questions from text using Machine Learning.
#计算机科学#该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。
#计算机科学#A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@月来客栈 出品
Sentiment analysis on Amazon Review Dataset available at http://snap.stanford.edu/data/web-Amazon.html
Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Ma...
#计算机科学#Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
OpenTextClassification is all you need for text classification! Open text classification for everyone, enjoy your NLP journey! 这可能是目前为止最全面的开源文本分类项目,支持中英双语、多种模型、多种任务。
#计算机科学#Aulas da Escola de Inteligência Artificial de São Paulo
#算法刷题#经典机器学习算法的极简实现
Research project aimed to classify the best stock research posts from r/WallStreetBets for you. 😏
#自然语言处理#中文文本分类实践,基于搜狗新闻语料库,采用传统机器学习方法以及预训练模型等方法
#计算机科学#Sentiment analysis with Machine Learning
#计算机科学#NaiveBayes classifier for JavaScript
#计算机科学#Source files for "Fun Q: A Functional Introduction to Machine Learning in Q"
#计算机科学#Heart Disease prediction using 5 algorithms
#计算机科学#Football Match prediction using machine learning algorithms in jupyter notebook