Pinned Repositories
-Machine-Learning-A-Probabilistic-Perspective-Kevin-P.-Murphy-Python-
《Machine Learning: A Probabilistic Perspective》(Kevin P. Murphy)中文翻译和书中算法的Python实现。
100_Days_of_ML_Code
These are the instructions for "100 Days of ML Code" By Siraj Raval on Youtube
A-Guide-for-Feature-Engineering-and-Feature-Selection-with-implementations-and-examples-in-Python.
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
algorithm-visualizer
:fireworks:Interactive Online Platform that Visualizes Algorithms from Code
alvito
Alvito - An Algorithm Visualization Tool for Python
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
Atom_notebook
Atom notebook
BDCI2019-SENTIMENT-CLASSIFICATION
CCF BDCI 2019 互联网新闻情感分析 复赛top1解决方案
BDCI_Car_2018
BDCI 2018 汽车行业用户观点主题及情感识别 决赛一等奖方案
book-Feature-Engineering-for-Machine-Learning
:book: [译] 面向机器学习的特征工程
Headonenjoy's Repositories
Headonenjoy/100_Days_of_ML_Code
These are the instructions for "100 Days of ML Code" By Siraj Raval on Youtube
Headonenjoy/Machine-learning-learning-notes
周志华《机器学习》又称西瓜书是一本较为全面的书籍,书中详细介绍了机器学习领域不同类型的算法(例如:监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等),记录了本人在学习过程中的理解思路与扩展知识点,希望对新人阅读西瓜书有所帮助!
Headonenjoy/feature-engineering-book
Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
Headonenjoy/Machine-Learning-Yearning-Chinese-ver
(完结)Andrew NG Machine-Learning-Yearning translation documents(吴恩达《Machine Learning Yearning》中文翻译及英文原稿)
Headonenjoy/xgboost_and_lightGBM_cheat_sheet
xgboost和lightGBM速查表
Headonenjoy/fastText-Quick-Start-Guide
fastText Quick Start Guide, published by Packt
Headonenjoy/sklearn-feature-engineering
使用sklearn做特征工程
Headonenjoy/Neural-Machine-Translation
English translation to French using Tensorflow seq2seq model
Headonenjoy/Machine-Learning-Mastery-With-Python
Following the instruction of "Machine Learning Mastery With Python"
Headonenjoy/zhihu-text-classification
[2017知乎看山杯 多标签 文本分类] ye组(第六名) 解题方案
Headonenjoy/Ensemble-Learning-in-Python
Headonenjoy/ML-Ensemble-Learning
An implementation of Ensemble Learning that uses (Weighted) Majority Voting
Headonenjoy/Spark-And-MLlib-Projects
This repository contains Spark, MLlib, PySpark and Dataframes projects
Headonenjoy/Kaggle-Competition-Give-Me-Some-Credit
Includes script for Kaggle Competition - Give Me Some Credit
Headonenjoy/spark-py-notebooks
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
Headonenjoy/Spark_SpamClassification
Using PySpark to classify text as spam or ham
Headonenjoy/Machine-Learning-with-Spark-Second-Edition
Machine Learning with Spark - Second Edition, by Packt
Headonenjoy/feature_engineering
特征工程
Headonenjoy/easy_seq2seq
[unmaintained] go to https://github.com/suriyadeepan/practical_seq2seq
Headonenjoy/Large-Scale-Machine-Learning
CS 565500 by Prof. Shan-Hung Wu at NTHU CS
Headonenjoy/thesis
Thang Luong's thesis on Neural Machine Translation
Headonenjoy/spark_machine_learning_tutorial
Tutorial on getting started with Spark and Machine Learning (delivered at the Big Data and Analytics Program, S P Jain)
Headonenjoy/parallel_ml_tutorial
Tutorial on scikit-learn and IPython for parallel machine learning
Headonenjoy/intrusionDetectionSystem
Headonenjoy/Server-log-Analysis-with-Apache-Spark
Server log analysis is an ideal use case for Spark. It's a very large, common data source and contains a rich set of information. Spark allows you to store your logs in files on disk cheaply, while still providing a quick and simple way to perform data analysis on them. This homework will show you how to use Apache Spark on real-world text-based production logs and fully harness the power of that data. Log data comes from many sources, such as web, file, and compute servers, application logs, user-generated content, and can be used for monitoring servers, improving business and customer intelligence, building recommendation systems, fraud detection, and much more.
Headonenjoy/spam-msg-classifier
A spam message classifier based on Naive Bayes.
Headonenjoy/Intro2SVM
Introduction to Support Vector Machines