Popular GitHub Repositories for Logistic

100 Days of ML Coding

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

The "Python Machine Learning (1st edition)" book code repository and info resource

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

Plain python implementations of basic machine learning algorithms

Text Classification Algorithms: A Survey

Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

Starter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and ?ukasz Kaiser offered by deeplearning.ai

AI比赛相关信息汇总

Deep-learning by using Pytorch. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.

Source code for my blog post "Getting started with TensorFlow on iOS"

??《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!

Learning to create Machine Learning Algorithms

Tool that predicts the outcome of a Dota 2 game using Machine Learning

Gender recognition by voice and speech analysis

Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).

Simple machine learning library / 簡單易用的機器學習套件

TextClf ：基于Pytorch/Sklearn的文本分类框架，包括逻辑回归、SVM、TextCNN、TextRNN、TextRCNN、DRNN、DPCNN、Bert等多种模型，通过简单配置即可完成数据处理、模型训练、测试等过程。