Experimentation with Neural Networks, as well as recommender systems related to movies.
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Updated
Aug 12, 2017 - Jupyter Notebook
Experimentation with Neural Networks, as well as recommender systems related to movies.
Weather prediction with Gaussian Process Regression
A working forecasting model to optimize promotions and warehouse stocks of one of the most important European retailers
Multiple linear regression model implementation with automated backward elimination (with p-value and adjusted r-squared) in Python and R for showing the relationship among profit and types of expenditures and the states.
Predict sales prices and practice different machine learning regressors.
Used historical usage patterns with weather data in order to forecast hourly bike rental demand.
It is an End to End Data Science project using Linear Regression Machine Learning model.
Solving Industry based and Solution based problems through Neural Networks
Intelligent systems Jupyter notebooks.
My Machine Learning course projects
Simple linear regressor that tries to approximate a simple function deployed in Tensorflow 2.0 without Keras
This repository is comprised of the Exploratory Data Analysis of the Body Fat data set from Kaggle. The feature engineering, hyperparameter tuning, and model training of the model. With comparative outlooks on the prediction vs actual results to understand and determine model accuracy.
Exploring hybride learning prototype
Machine Learning model to predict the price of a house taking a few parameters like crime rate, number of rooms etc. Uses a pre-existing dataset from the UCI ML repository for training the model.
Gradient Boosting prediction for the profit of 50 american startups
Implementation of a Partial Least Squares Regressor
Application and Evaluation of Genetic Algorithms on Decision Trees. A project for the course of Software Dependability at University of Salerno.
国内基金数据获取及回归排名
Fast regression and mediation analysis of vertex or voxel MRI data with TFCE
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