sandy4321 Goto Github PK

si_hackathon

Repo for my May 16th Sports Illustrated Hackathon Presentation

simple_adpcm

Implementação simplificada do algoritmo de compressão de áudio ADPCM

simple_ads_clickfraud_detection

This is a simple POC of using Dempster Shafer theory for counter click fraud

simple_esn

simple Echo State Networks integrated with scikit-learn

simple_tasks_python

simpletestssp

RTB - simple SSP platform for testing DSP

simplex_algorithm

Simplex algorithm - can handle minimization and maximization problems with several variables under linear constraints. (Collaboration/help requested)

simranklowrank

Implementation of the SimRank lowrank approximation

simulating_spx_returns

Simulating returns and crash risk for the S&P500 Index using long-run historical data, as published in Towards Data Science on Medium.com

siraj_course_how-to-do-linear-regression-using-gradient-descent

# linear_regression_live This is the code for the "How to Do Linear Regression the Right Way" live session by Siraj Raval on Youtube ## Overview This is the code for [this](https://youtu.be/uwwWVAgJBcM) video on Youtube by Siraj Raval. I'm using a small dataset of student test scores and the amount of hours they studied. Intuitively, there must be a relationship right? The more you study, the better your test scores should be. We're going to use [linear regression](https://onlinecourses.science.psu.edu/stat501/node/250) to prove this relationship. Here are some helpful links: #### Gradient descent visualization https://raw.githubusercontent.com/mattnedrich/GradientDescentExample/master/gradient_descent_example.gif #### Sum of squared distances formula (to calculate our error) https://spin.atomicobject.com/wp-content/uploads/linear_regression_error1.png #### Partial derivative with respect to b and m (to perform gradient descent) https://spin.atomicobject.com/wp-content/uploads/linear_regression_gradient1.png ## Dependencies * numpy Python 2 and 3 both work for this. Use [pip](https://pip.pypa.io/en/stable/) to install any dependencies. ## Usage Just run ``python3 demo.py`` to see the results: ``` Starting gradient descent at b = 0, m = 0, error = 5565.107834483211 Running... After 1000 iterations b = 0.08893651993741346, m = 1.4777440851894448, error = 112.61481011613473 ``` ## Credits Credits for this code go to [mattnedrich](https://github.com/mattnedrich). I've merely created a wrapper to get people started.

sirius2017

sisbid

Notes for workshop

sispa-mers

Expert System Mers-CoV Dempster-Shafer

sk2torch

Convert scikit-learn models to PyTorch modules

skater

Python Library for Model Interpretation/Explanations

skbbank

Курс по ML

skflow

Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning

skift

scikit-learn wrappers for Python fastText.

skillfactory_ml

http://skillfactory.ru/ml-programma-machine-learning

sklearn-crfsuite

scikit-learn inspired API for CRFsuite

sklearn-deap

Use evolutionary algorithms instead of gridsearch in scikit-learn

sklearn-genetic

Genetic feature selection module for scikit-learn

sklearn-hogwild

An implementation of the Hogwild! algorithm for asynchronous SGD that interfaces with sci-kit learn.

sklearn-oblique-tree

a python interface to OC1 and other oblique decision tree implementations

sklearn-pandas

Pandas integration with sklearn

sklearn-porter

Transpile trained scikit-learn estimators to C, Java, JavaScript and others.

sklearn-weka-naivebayes-decisiontree

Built predictive models of a categorical nursery dataset and a continuous leaf dataset using naive bayes and decision tree models in SKLearn and WEKA

sklearn_europython_2014

Scikit-learn Tutorial at EuroPython 2014

sklearn_nestedcv

Sklearn wrapper for Nested CrossValidation

sklearndf

DataFrame support for scikit-learn.