AI course Notebooks and Exercises

Apache Hadoop development environment integrated with Jupyter Notebook using Docker

Local playground for Spark and Jupyter notebooks, plus Iceberg support

Exercise of using the Streaming API with Hadoop to determine the word count of Wikipedia articles.

Hadoop beginner exercise in analyzing European football teams' statistics over the last 20 years. The goal is to determine which team had the highest win percentage-rate.

Simple examples of using spark RDDs with a remote jupyter notebook

Simple notebook illustrating Hadoop example with map reduce on a large file for big data.

Stack to run Zeppelin notebooks over Hadoop and Spark

收录了大数据相关各类资料、笔记、手册

This repository contains a lab report and supporting scripts/notebooks that explore Big Data and NoSQL technologies, including Neo4j, mongoDB and Hadoop

This repository contains my hands-on journey through the Big Data training by NTI. Includes labs, notebooks, and notes on tools like HDFS, Spark, Kafka, Flink, Hive, HBase and more.

hdp-notebook

Recently updated with 50 new notebooks! Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

A spark cluster configuration with the Apache Toree notebook

This is the final project I had to do to finish my Big Data Expert Program in U-TAD in September 2017. It uses the following technologies: Apache Spark v2.2.0, Python v2.7.3, Jupyter Notebook (PySpark), HDFS, Hive, Cloudera Impala, Cloudera HUE and Tableau.

重庆大学2024年秋大数据架构与技术课程，本仓库基于学校提供的原开源项目进行了优化和扩展，包含最新的工具版本、简化的环境配置流程、以及对更便捷高效的开发工具（如 Jupyter Notebook）的全面支持。

c++, data_analysis, deep_learning, docker, git, python etc.

Hadoop environment with HDFS, Spark, Hue, Jupyter Notebooks, etc. all installed in docker-compose

📓 [Active] Portafolio of data science projects. Using: Python, PyTorch, Spark, Tensorflow, Scikit, Keras. Includes Classification, Regression, Time series, NLP, Deep learning, among others.

Jupyter Notebook showing how to process Telecom datasets using PySpark (SparkSQL and DataFrames) and plotting the results using Matplotlib.