sandy4321 Goto Github PK

week-7-ip

Overview As a Data Scientist, you work for Hass Consulting Company which is a real estate leader with over 25 years of experience. You have been tasked to study the factors that affect housing prices using the given information on real estate properties that was collected over the past few months. Later onwards, create a model that would allow the company to accurately predict the sale of prices upon being provided with the predictor variables. Within your deliverable you are expected to: Define the question, the metric for success, the context, experimental design taken. Read and explore the given dataset. Define the appropriateness of the available data to answer the given question. Find and deal with outliers, anomalies, and missing data within the dataset. Perform univariate, bivariate and multivariate analysis recording your observations. Performing regression analysis. Incorporate categorical independent variables into your models. Check for multicollinearity Provide a recommendation based on your analysis. Create residual plots for your models, and assess heteroskedasticity using Barlett's test. Challenge your solution by providing insights on how you can make improvements in model improvement. While performing your regression analysis, you will be required to perform modeling using the given regression techniques then evaluate their performance. You will be then required to provide your observations and recommendation on the suitability of each of the tested models on their appropriateness of solving the given problem. Multiple Linear Regression Quantile Regression Ridge Regression Lasso Regression Elastic Net Regression

weibull-adstock

Modeling adstock in media mix modeling using Weibull transformations.

weight-loss

Machine Learning meets ketosis: how to effectively lose weight

weighted_knn_classification

Code for "Multiclass Classification via Class-Weighted Nearest Neighbors"

weightwatcher

The WeightWatcher tool for predicting the accuracy of Deep Neural Networks

weighwords

Python library for creating word clouds from text

weirdhta

A python tool to create obfuscated HTA script.

west-nile-virus-prediction

Kaggle competition - Predict West Nile virus in mosquitos across the city of Chicago

west_nile_virus_2015

the 2nd place solution for West Nile Virus Prediction challenge on Kaggle

wfm

Weighted Factorization Machines

what-if-tool

Source code/webpage/demos for the What-If Tool

what_do_you_recommend

recommender systems for books

whats_cooking

where-are-you-tweeting-from-

Use of Naiive Bayes Text Classification and Mutual Information Feature selection to predict from what major city region a twitter user is tweeting

whilemymcmcgentlysamples

my blog

whisper

Whisper is a file-based time-series database format for Graphite.

whisper-oct2023

Robust Speech Recognition via Large-Scale Weak Supervision

who-stole-the-postage-

Who Stole the Postage? Fraud Detection in Return-Freight Insurance Claims

who_is_resigning

Human resources data mining with machine learning algorithms

why-to-choose-warehouse-management-software

Why to choose Warehouse Management Software Warehouse management software is one of the features which enhances the overall inventory management software to increase the productivity of the business. From managing the overall stock in the inventory to systematically managing them in proper groups, everything is worked in a streamlined manner to avoid any kind of hassles in the whole inventory process. Reasons to choose warehouse management software · Helps in tracking inventory and customers at the same time · Enhances business productivity · Helps in catalog management · Provides barcoding facility which helps in assessing the goods easily · Provides robust reporting Have a look at TYASuite India’s 1st plug and play Warehouse Management Software which lets you organize your warehouse clutter-free and also boost the supply chain by fulfilling the orders on time. Get the Free Trial Version now!

whydeeplearningworks

whynot

A Python sandbox for decision making in dynamics

wian

AMIA submission examining note-derived vector representations

wide_deep

Wide and Deep Neural Network For Reccomendation Systems

wids_datathon_2020

Code used to solve Kaggle competition on WiDS Datathon 2020

wiki-detox

See https://meta.wikimedia.org/wiki/Research:Modeling_Talk_Page_Abuse

wiki-pagecounts-merge

Python scripts to download and merge Wikipedia.org page count dumps into a single file

wiki-telegram-bot

wikiart

Full retriever for art and metadata in http://wikiart.org/

wikiedits

Automatic extraction of edited sentences from text edition histories.