304 Open source projects that are alternatives of or similar to receiptdID

ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

Word2Vec iOS port

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

A fast and easy to use decision tree learner in java

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

Bag of words meets bags of popcorn in Python 3 中文教程

Handwritten Digit Recognition using Machine Learning and Deep Learning

Implementation of Grad-CAM for text.

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

Small JavaScript implementation of ID3 Decision tree

Heart Disease prediction using 5 algorithms

several methods for text classification

This is the official implementation for the paper 'AutoEncoder by Forest'

A set of tools to understand what is happening inside a Random Forest

Recommendation based on sequence

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

ML-powered Loan-Marketer Customer Filtering Engine

YouTube Like Count Predictions using Machine Learning

Language Modeling and Text Classification in Malayalam Language using ULMFiT

A New, Interactive Approach to Learning Data Science

Machine Learning library written in Python and NumPy.

Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

Exploring the simple sentence similarity measurements using word embeddings

This is the implementation of Sparse Projection Oblique Randomer Forest

Building Decision Trees From Scratch In Python

skip-gram for Chinese word2vec base on tensorflow

🍊 📊 💡 Orange: Interactive data analysis

document embedding and machine learning script for beginners

An end-to-end machine learning and data mining framework on Hadoop

A two-stream convolutional neural network for learning abitrary similarity functions over two sets of training data

InfiniteBoost: building infinite ensembles with gradient descent

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

An unofficial implementation of asm2vec as a standalone python package

Machine Learning inference engine for Microcontrollers and Embedded devices

Conformalized Quantile Regression

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

code for "Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering" ACL 2017

A collection of research papers on decision, classification and regression trees with implementations.

Scripts demo-ing how to train a Word2Vec model and reduce its vector space

随机森林，Random Forest（RF）

A random forest

Creating word embeddings from scratch and visualize them on TensorBoard. Using trained embeddings in Keras.

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

An evaluation of word-embeddings for classification

Text Classification Algorithms: A Survey

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'

Hyperstar: Negative Sampling Improves Hypernymy Extraction Based on Projection Learning.

Reproduce research from paper "Predicting the direction of stock market prices using random forest"

RUSSE: Russian Semantic Evaluation.

Scripts, tools and example data for mapping wetland ecosystems using data driven R statistical methods like Random Forests and open source GIS

Word2Vec encodings based search engine for Stackoverflow questions

Misc Statistics and Machine Learning codes in R

Graph Embedding via Frequent Subgraphs