quadratic-discriminant-analysis

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

Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine

Final Year project based upon Network Intrusion Detection System

This is a binary classification problem related with Autistic Spectrum Disorder (ASD) screening in Adult individual. Given some attributes of a person, my model can predict whether the person would have a possibility to get ASD using different Supervised Learning Techniques and Multi-Layer Perceptron.

Iris classification with Python Scikit-learn 🌼

Machine learning library for classification tasks

Training ensemble machine learning classifiers, with flexible templates for repeated cross-validation and parameter tuning

Machine learning library for classification tasks

Gaussian Discriminant Analysis introduction and Python implementation from scratch

Tour of Machine Learning Algorithms for Binary/Multiclass Classification

Probabilistic graphical models home works (MVA - ENS Cachan)

Machine learning library for classification tasks

The projects are part of the graduate-level course CSE-574 : Introduction to Machine Learning [Spring 2019 @ UB_SUNY] . . . Course Instructor : Mingchen Gao (https://cse.buffalo.edu/~mgao8/)

Comitê de Classificadores | Projeto N1

Overview of statistical learning methods for classification

To Detect Sepsis Disease using six Classifiers on clinical data

Recognize users of mobile devices from accelerometer data ( Accelerometer Biometric Competition on kaggle)

Built an ML-based HR analytics solution to predict employee turnover. Used SMOTEENN and models like Random Forest, SVM, Logistic Regression, KNN, among others. Optimized with GridSearchCV and RandomizedSearchCV. Visualized insights in Tableau to support retention strategies.