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blog

A collection of resources and Jupyter notebooks from my blog.

boostaroota

A fast xgboost feature selection algorithm

cheatsheet

Cheatsheet

classical-piano-composer

cnnpluslstm

Based on http://aqibsaeed.github.io/2016-11-04-human-activity-recognition-cnn/ and lstm

corae

csc301

Lecture notes for the course "Fundamentals of Programming Languages" at the University of Rhode Island.

csc402

Lecture notes for 'Programming Language Implementation' course at the University of Rhode Island

csc544

slides and resources for CSC544 @ URI (Theory of Computation)

csc581

Graduate Machine Learning Course at the University of Rhode Island

data-mining-project

Recognizing human activity using multiple wearable accelerometer sensors placed at different body positions.

dealing-with-imbalanced-data

Using Imblearn To Tackle Imbalanced Data Sets

deep-learning-for-human-activity-recognition

deep-learning-samples

Sample code for deep learning & neural networks

deep_dive_in_ml_python

This repository comprises the Jupyter Notebooks of my blogging series "Deep Dive in Machine Learning with Python".

demo-self-driving

Streamlit app demonstrating an image browser for the Udacity self-driving-car dataset with realtime object detection using YOLO.

digitalsignalprocessing

Materials for the DSP course I teach at the Donetsk National University

dimensionality_reduction_techniques

This repository is created for understanding and explaining the various dimensionality reduction techniques on real datasets.

dog_features_extraction

features extraction from dog accelerometer data

dream_pd

Code used in the Parkinsons Disease Digital Biomarker DREAM Challenge

feature

Feature Selection

feature-engineering

feature-engineering-and-feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

feature-engineering-made-easy

Feature Engineering Made Easy, published by Packt

feature-selection

Features selector based on the self selected-algorithm, loss function and validation method

feature-selection-1

feature-selection-2

feature-selection-3

feature-selection-4

feature-selection-5

The objective of this task is to assess the impact of feature selection on training and test datasets.