Forward and backward feature selection with adjusted R squared in R

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

主要包含ModelHelper和NLPHelper，其中ModelHelper主要有特征选择、超参数搜索、模型解释和模型融合等，NLPHelper则是进一步封装了NLP一些常用的操作，常用的网络结构以及几个NLP的任务

EDA

This Repository Contains Different Machine Learning and Important Concepts

FeatEngX is an automated Feature Engineering Tool used by Data Engineers & AI Researchers for making feature selection process, data preprocessing, and engineering accurate.

In this project we will work with housing data for the city of Ames, Iowa, United States from 2006 to 2010. You can read more about why the data was collected here (https://doi.org/10.1080/10691898.2011.11889627). You can also read about the different columns in the data here (https://www.tandfonline.com/doi/abs/10.1080/10691898.2011.11889627).

AlmaBetter Capstone Project - Unsupervised ML. Developed a book recommendation system for Amazon customers using memory and model based collaborative filtering by utilizing the description of book consumed and user interests.

Particle Swarm Optimization (PSO) - Feature Selection and Hyperparameter Tuning

This repository describes the methods used to test different sci-kit learn feature selection methods as part of Qiime2 q2-classifier.

Giving a song dataset, thorough exploratory analysis, diverse model construction, and innovative feature engineering to developing predictive models for song scoring.

Data science project applying feature selection/dimensionality reduction techniques to identify the explanatory variables to be included within a linear regression model that predicts the number of times an online news article will be shared using Python 3 in a Juypter Notebook.

Data Science - Random Forest Work

Data Science - Neural Networks Work

A smart Network Intrusion detection tool to perform forensics on your network.

Machine Learning Algorithm : outlier identifying, feature selection

ML hyperparameters tuning and features selection, using evolutionary algorithms.