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applied_bayesian_statistics

This Repository will have code for Bayesian data Analysis

automaticvaluationmodel

Automated valuation model (AVM) is the name given to a service that can provide real estate property valuations using mathematical modelling combined with a database. Most AVMs calculate a property’s value at a specific point in time by analyzing values of comparable properties. Some also take into account previous surveyor valuations, historical house price movements and user inputs (e.g. number of bedrooms, property improvements, etc.).

chatbot-ui

An open source ChatGPT UI.

crm-analytics

The efficient market hypothesis suggests that practically it is impossible to predict the customer’s behaviors in B2B or B2C firms. But also, there are number of firms who are doing this very efficiently through the myriad information of past customers’ data and through the sophisticated use of data analytics.

cv

dataopen-2018

Traditionally the data captured from the NYC Taxi & Limousine commission was physically analysed by various analyst to find the superlative practice to follow and derives the output from it which would eventually aids the people who commute via taxis. Later during early 2000 the taxi services where exponentially developed and the data capture by NYC was in GB’s, which was very difficult to analyse manually. To overcome these hitches BigData was under the limelight to analyse such a colossal dataset.

drowsy_driving

Safety has received an unprecedented amount of research attention in recent years, particularly in relation to transportation. Transportation safety research has typically focused on increasing the level of safety for drivers and their surroundings, aiming to reduce the high number of road accidents.

eda_new_library

feature-engineering-and-feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

feature-selection

Features selector based on the self selected-algorithm, loss function and validation method

fine_tuning_experiments

Experiments of fine tuning

first-project

functional_library

hello-world

First Repository

hermes-function-calling

housing_price_prediction

Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence. With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.

idea_connect

inventory_analytics

Inventory optimization is the provision of the right inventory, in the right quantities and at the right locations, to meet the supply and demand of parts and materials in the enterprise. Significant benefits exist for organizations that optimize their inventory by reducing inventory items and stock levels, thus avoiding associated carrying costs and obsolescence write-downs. Indirectly, organizations can generate savings by using time formerly spent on inventory management to ensure physical assets’ reliability and availability.

islr---r-codes

Statistical Learning refers to a set of tools for modeling and understanding complex dataset. These codes are from book ISLR and their exercise. Play with it at your will.

islr-python

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

jayshah5696.github.io

Portfolio website for jay shah

kaggle_homedepot

Shoppers rely on Home Depot’s product authority to find and buy the latest products and to get timely solutions to their home improvement needs. From installing a new ceiling fan to remodeling an entire kitchen, with the click of a mouse or tap of the screen, customers expect the correct results to their queries – quickly. Speed, accuracy and delivering a friction less

kaggle_mercedes

Since the first automobile, the Benz Patent Motor Car in 1886, Mercedes-Benz has stood for important automotive innovations. These include, for example, the passenger safety cell with crumple zone, the airbag and intelligent assistance systems. Mercedes-Benz applies for nearly 2000 patents per year, making the brand the European leader among premium car makers. Daimler’s Mercedes-Benz cars are leaders in the premium car industry. With a huge selection of features and options, customers can choose the customized Mercedes-Benz of their dreams.

langchain-tutorials

Overview and tutorial of the LangChain Library

ml-design-docs

📄 Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)

nd-empowerment

Support NeuroDiversity Month

news_article_recommendation

Objective of the project is to build a hybrid-filtering personalized news articles recommendation system which can suggest articles from popular news service providers based on reading history of twitter users who share similar interests (Collaborative filtering) and content similarity of the article and user’s tweets (Content-based filtering).

notes

Notes on data science, machine learning, artificial intelligence, history, and social science.

phase1_analysis

The project is based on a set of data collected from a manufacturing process, in which both in-control and out-of-control data are present. You are asked to develop a method or a procedure to identify the data falling in the respective categories, i.e., which ones are in-control and which ones out of control. This is amounted to a Phase I analysis, whose purpose to isolate the in-control data for estimating the in-control distribution parameters so that a monitoring scheme can be set up for future missions.

power_curve_estimation

Wind energy is one of the fastest growing renewable energy sources. According to a report issued by the U.S. Department of Energy (DOE), wind power installation in the United States increased by nearly a factor of 10 in the past decade, from 6350 megawatts (MW) in 2003 to 61,108 MW by the end of 2013 (DOE 2014). The DOE advocates working toward the goal that wind power accounts for 20% of the total electricity generated in the United States by 2030 (DOE 2008).