机器学习教程，本教程包含基于numpy、sklearn与tensorflow机器学习，也会包含利用spark、flink加快模型训练等用法。本着能够较全的引导读者入门机器学习。

Sentiment Analysis and Data Visualization

Application of Sentiment Analysis of Italian tweet with Python and Spark

A Spark Streaming implementation for Online Twitter Sentiment Analysis.

Efficiently tackle large datasets and perform big data analysis with Spark and Python

In this project I stream data and do crime classification using Spark. This dataset contains incidents derived from the SFPD Crime Incident Reporting system. The data ranges from 1/1/2003 to 5/13/2015. I do some data analysis of crime scenes in different areas and with respect to other parameters.

Apache Spark is one of the most widely used and supported open-source tools for machine learning and big data. In this repo, discover how to work with this powerful platform for machine learning. This repo discusses MLlib—the Spark machine learning library—which provides tools for data scientists and analysts who would rather find solutions to b…

Graduation project categorizes popular search phrases using Python and Spark and presents them on a website to inspire creators.

对Spark ML进行二次封装，提供api调用

A movie recommender system using user-based collaborative filtering algorithm.

Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph p…

Ophelia a PySpark analytics wrapper.

Development of an AutoML System to Predict the Compressive Strength of Concrete

Using the Thunder Library for Image Processing with Spark ML Lib

This repo contains code for restuarant recommendation system for users based upon business rating value.

Pequenos projetos utilizando ferramentas do ecossistema Apache Hadoop

Implemented an auto-clustering tool with seed and number of clusters finder. Optimizing algorithms: Silhouette, Elbow. Clustering algorithms: k-Means, Bisecting k-Means, Gaussian Mixture. Module includes micro-macro pivoting, and dashboards displaying radius, centroids, and inertia of clusters. Used: Python, Pyspark, Matplotlib, Spark MLlib.

Yelp Toronto User Pattern Analysis and Recommender System