Starred repositories
Efficient Deep Learning for Stereo Matching Tensorflow 2.x
An implementation of the classic stereo vision Block Matching(BM) algorithm. Python version
⚡机器学习实战(Python3):kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
PyTorch implementation of image classification models for MNIST
A deep learning project written in PyTorch, intended as a comparison between a convolutional neural network, recurrent neural network and ConvNet + LSTM for image recognition on MNIST dataset.
Classify MNIST image dataset into 10 classes. Build an image classifier with Recurrent Neural Network (RNN: LSTM) on Tensorflow.
The Optical Character Recognition (OCR) system consists of a comprehensive neural network built using Python and TensorFlow that was trained on over 115,000 wordimages from the IAM On-Line Handwrit…
cnn+rnn: vgg(vgg16,vgg19)+rnn(LSTM, GRU), resnet(resnet_v2_50,resnet_v2_101,resnet_v2_152)+rnnrnn(LSTM, GRU), inception_v4+rnn(LSTM, GRU), inception_resnet_v2+rnn(LSTM, GRU),.....
CS777 Big Data Analytics Project - LDA Topic Modeling with Gibbs Sampling on Twitter Data
Implementation of Spark code in Jupyter notebook. Topics include: RDDs and DataFrame, exploratory data analysis (EDA), handling multiple DataFrames, visualization, Machine Learning
Tutorial for Topic Modelling using PySpark and Spark NLP
NLP Topic Modeling Techniques (LDA, LSA & BERTopic)
Topic prediction using LSA modeling.
Famous 20 newsgroups documents are compared for similarity using scikitlearn library
Apache Spark - A unified analytics engine for large-scale data processing
PySpark Python ML Models
PySpark实战指南(Leaning PySpark)代码
使用python抓取微博数据并对微博文本分析和可视化,LDA(树图)、关系图、词云、时间趋势(折线图)、热度地图、词典情感分析(饼图和3D柱状图)、词向量神经网络情感分析、tfidf聚类、词向量聚类、关键词提取、文本相似度分析等
KMeans, Cure and Canpoy algorithms are demonstrated using Pyspark.
KMeans Clustering and PCA using Pyspark
Java calls the KMeans algorithm which is implemented by Tensorflow in Python, and stores the returns in Dataframe format of Spark.
Java 1-21 Parser and Abstract Syntax Tree for Java with advanced analysis functionalities.