JingwuChen's repositories
aas
Code to accompany Advanced Analytics with Spark from O'Reilly Media
AiLearning
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
airflow-scheduler-failover-controller
A process that runs in unison with Apache Airflow to control the Scheduler process to ensure High Availability
awesome-network-analysis
A curated list of awesome network analysis resources.
awesome-spark
A curated list of awesome Apache Spark packages and resources.
Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
deeplearning_ai_books
deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）
elasticsearch-spark-recommender
Use Jupyter Notebooks to demonstrate how to build a Recommender with Apache Spark & Elasticsearch
FastChat
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
HFT-CNN
Convolutional Neural Network based on Hierarchical Category Structure for Multi-label Short Text Categorization
ijcai-2018
ijcai-2018 top1 solution
kafka-streams-machine-learning-examples
This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.
learning-apache-spark
Notes on Apache Spark (pyspark)
Optimus
:truck: Agile Data Science Workflows made easy with Python and Spark.
pyspark-asyncactions
Asynchronous actions for PySpark
python_data_structures_and_algorithms
Python 中文数据结构和算法教程
reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
spark-sandbox
A playground for Spark jobs.
spark-sklearn
Scikit-learn integration package for Apache Spark
spark2.0-examples
Examples of Spark 2.0
SparkStreamSources
Spark Custome Stream Source and Sink
tensorflow-linux-wheel
(cuda9.2 +cudnn7.1.4 )Performance-optimized wheels for TensorFlow On Linux System
tensorflow_reading_data
this is just a practice
xgboost-smote-detect-fraud
Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in this scenario? Find the answers in this code pattern!