nchams Goto Github PK

bisection-method

Bisection method for finding roots

calculator-in-python

Simple Calculator in Python

classifying-pediatric-skin-condtions

Classifying Images of Pediatric Skin Conditions with Deep Learning

code_snippets

coursera-deep-learning

My notes / works on deep learning from Coursera

credit-risk-modelling

Modelling Creditworthiness with Deep Learning

datasharing

The Leek group guide to data sharing

ev_charging

algorithm for optimal ev charging station locations

git4noobs

A swift intro to Git and GitHub for noobs

gradient-descent

Linear regression optimized with gradient descent algorithm

individual-household-electric-power-consumption-data-set-

Individual household electric-power consumption Data Set (LSTM) [tutorial]

islr

My Python code for labs and exercises in the book "An Introduction to Statistical Learning with Applications in R".

islr-python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

k-means-clustering

learning-from-data-solutions

Repository of my solutions to the problems of "Learning from Data"

linear-regression

Linear regression in R

logistic-regression

Tissues classification using Logistic Regression.

lstm_autoencoder_classifier

An LSTM Autoencoder for rare event classification

machine-learning-coursera

Completed assignments from Coursera's Machine Learning Course.

machine_learning_projects

matlab

Matlab/Octave scripts I wrote as a part of a course on Numerical Analysis, using Burden & Faires

mds

Marketing Data Science

mlp-classifier-

MLP classifier

mlwr

Machine Learning with R

nchams

Config files for my GitHub profile.

neural_network

Prediction using an Feed-Forward Neural Network built from scratch

newtons-method

Newtons Method to approximate the roots of a polynomial

numerical_analysis

Timothy Sauer - Numerical Analysis(2nd edition); Solution to computer problems.

predicting-motorized-vehicles

predictive_modeling_price

Data Analysis and Machine Learning with Python: EDA with ECDF and Correlation analysis, Preprocessing and Feature engineering, L1 (Lasso) Regression and Random Forest Regressor with scikit-learn backed up by cross-validation, grid search and plots of feature importance.