peppyguy Goto Github PK

2015

Public material for CS109

2015lab1

2018aicity_teamuw

The winning method in Track 1 and Track 3 at the 2nd AI City Challenge Workshop in CVPR 2018 - Official Implementation

aaic-notes

These are my personal notes, feel free to use them for your reference.

actionai

custom human activity recognition modules by pose estimation and cascaded inference using sklearn API

agricultural-price-prediction-and-visualization-on-android-app

In Agriculture Price Monitioring , I have used data provided by open government site data.gov.in, which updates prices of market daily . Working Interface Details: We have provided user choice to see current market prices based on two choices: market wise or commodity wise use increase assesibility options. Market wise: User have to provide State,District and Market name and then select market wise button. Then user will be shown the prices of all the commodities present in the market in graphical format, so that he can analyse the rates on one scale. This feature is mostly helpful for a regular buyer to decide the choice of commodity to buy. He is also given feature to download the data in a tabular format(csv) for accurate analysis. Commodity Wise: User have to provide State,District and Commodity name and then select Commodity wise button. Then user will be shown the prices of all the markets present in the region with the commodity in graphical format, so that he can analyse the cheapest commodity rate. This feature is mostly helpful for wholesale buyers. He is also given feature to download the data in a tabular format(csv) for accurate analysis. On the first activity user is also given forecasting choice. It can be used to forecast the wholesale prices of various commodities at some later year. Regression techniques on timeseries data is used to predict future prices. Select the type of item and click link for future predictions. There are 3 java files Forecasts, DisplayGraphs, DisplayGraphs2 ..... Please change the localhost "server_name" at time of testing as the server name changes each time a new server is made. Things Used: We have used pandas , numpy , scikit learn , seaborn and matplotlib libraries for the same . The dataset is thoroughly analysed using different function available in pandas in my .iPynb file . Not just in-built functions are used but also many user made functions are made to make the working smooth . Various graphs like pointplot , heat-map , barplot , kdeplot , distplot, pairplot , stripplot , jointplot, regplot , etc are made and also deployed on the android app as well . To integrate the android app and machine learning analysis outputs , we have used Flask to host our laptop as the server . We have a separate file for the Flask as server.py . Where all the the necessary stuff of clint request and server response have been dealt with . We have used npm package ngrok for tunneling purpose and hosting . A different .iPynb file is used for the time series predictions using regression algorithms and would send the csv file of prediction along with the graph to the andoid app when given a request .

ai-predictivemaintenance

allstate_capstone

Allstate Kaggle Competition ML Capstone Project

amazon-product-recommender-system

Sentiment analysis on Amazon Review Dataset available at http://snap.stanford.edu/data/web-Amazon.html

analytics_vidhya

Codes related to activities on AV including articles, hackathons and discussions.

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

anomaly_detection

applied-ai-course

applied_ai_course_notes

appliedaicourse-assignmentandnotes

This repo contains the Applied Ai Course Assignments and Notes.

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

autoarima-time-series-blog

This is the code notebook for the blog post on using Python and Auto ARIMA

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-python-data-science

Probably the best curated list of data science software in Python.

bellkoralgorithm

A Python implementation of the Bellkor Algorithm

bottles

cars

clothing-recommender

ML

cloudml-samples

Cloud ML Engine is now a part of AI Platform

complete-python-3-bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

computer-vision-advanced

content

Official content for Harvard CS109

corporacion-favorita-grocery-sales-forecasting-kaggle

forecasting project @ Forcasting-models course at Korea Univ.

cracking-the-data-science-interview

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep