peppyguy's repositories
Predictive_Maintenance_using_Machine-Learning_Microsoft_Casestudy
Predictive_Maintenance_using_Machine-Learning_Microsoft_Casestudy
AutoArima-Time-Series-Blog
This is the code notebook for the blog post on using Python and Auto ARIMA
deep-learning-coursera-complete
Deep Learning Specialization by Andrew Ng on Coursera - My Completed Coursework Repo - All 5 Courses
python-data-cleaning
Jupyter Notebooks and datasets for our Python data cleaning tutorial
Kaggle-Competition-Favorita
5th place solution for Kaggle competition Favorita Grocery Sales Forecasting
BellkorAlgorithm
A Python implementation of the Bellkor Algorithm
DL4CVStarterBundle
Edited code examples from the book 'Deep Learning for Computer Vision - Starter Bundle' by Adrian Rosebrock
PracticalPythonAndOpenCV_CaseStudies
Edited code examples from the book 'Practical Python and OpenCV - Case Studies (3rd Edition)' by Adrian Rosebrock
Sky-Cast-Capstone
Sky Cast: A Comparison of Modern Techniques for Forecasting Time Series
SQL-for-Data-Science
Coursera - University of California, Davis
datacamp_facebook_live_ny_resolution
In this Facebook live code along session with Hugo Bowne-Anderson, you're going to check out Google trends data of keywords 'diet', 'gym' and 'finance' to see how they vary over time.
Practical-Time-Series-Analysis
Practical Time-Series Analysis, published by Packt
Grocery_sales_forecasting
This project is based on a challenge posted on kaggle.com. It is about prediction product sales for Corporación Favorita(CF) . CF is one of the Ecuadorian-based grocery retailers, operating hundreds of stores, with over 200,000 different products which includes perishable products also such as egg,milk etc. They need good estimated sale of each product so that they can purchase and update inventory accordingly. This estimate eventually benefits two ways to FC. One, help FC not to overstock under popular products specifically perishables and another is have enough inventory in anytime for each product so that customers do not disappointed because not having stock of product.
SALES-FORECASTING-OF-RETAIL-CLOTHING-PRODUCT-CATEGORIES
Retail is one of the most important business domains for data science and data mining applications because of its prolific data and numerous optimization problems such as optimal prices, discounts, recommendations, and stock levels that can be solved using data analysis methods.
Amazon-Product-Recommender-System
Sentiment analysis on Amazon Review Dataset available at http://snap.stanford.edu/data/web-Amazon.html
Future_Datathon
This is a machine learning challenge conducted by C&D Labs and Future Group in association with HackerEarth.
python_and_excel
tutorials and notebooks on using python where excel fails or in combination with excel
Shiny-App
A shiny interface for ML models, data visualization etc.
Kaggle
Codes for Kaggle Competitions
Analytics_Vidhya
Codes related to activities on AV including articles, hackathons and discussions.
Wallmart_Sales_Predictions
Machine learning project on predicting sales for Wallmart stores
Udacity-ML-Capstone
Udacity Machine Learning Nanodegree Capstone Project
Rossman-Stores-Sales-Prediction-using-Python-R
This project mainly focuses on building a predictive model to predict the sales of 1115 rossman stores across Germany.