airbnb-booking-analysis

Airbnb data analytics is a qualitative and quantitative processes and techniques used to enhance productivity, marketing strategies, occupancy rates, and yield. The Airbnb company has provided with the past data to come up with the insightful business strategy. The major target of the project is to provide data analysis techniques to draw out key features of the market from the datasets. The initial task is to understand the dataset and discuss the problem. Looking towards the factor how region, room type, price, location etc. can helpful to the problem. The next task is to data analysis parts based on bookings on different view, market segment and many more to draw a proper conclusions and results.

awesome-readme

A guide to writing an Awesome README. Read the full article in Towards Data Science.

bike-sharing-demand-prediction

Currently Rental bikes are introduced in many urban cities for the enhancement of mobility comfort. It is important to make the rental bike available and accessible to the public at the right time as it lessens the waiting time. Eventually, providing the city with a stable supply of rental bikes becomes a major concern. The crucial part is the prediction of bike count required at each hour for the stable supply of rental bikes.

book-recommendation-system

A recommendation engine is a class of machine learning which offers relevant suggestions to the customer. A recommendation system is one of the top applications of data science. Every consumer Internet company requires a recommendation system like Netflix, YouTube, a news feed, etc. What you want to show out of a huge range of items is a recommendation system. Before the recommendation system, the major tendency to buy was to take a suggestion from friends. But Now Google knows what news you will read, YouTube knows what type of videos you will watch based on your search history, watch history, or purchase history. We were provided with ‘Book Recommendation System’ dataset to perform machine learning task, were to get insights from users-items interactions and provide best recommendation to users.

business-kpi-tableau-dashboard

creating-python-package

eda-data-plots

flask-api

In this repo I show how to simple create an API for your machine learning models in Python

flask-application-fastapi-intro-almabetter

The Python micro framework for building web applications.

health-insurance-cross-sell-prediction

An insurance policy is an arrangement by which a company undertakes to provide a guarantee of compensation for specified loss, damage, illness, or death in return for the payment of a specified premium. A premium is a sum of money that the customer needs to pay regularly to an insurance company for this guarantee. We were provided with ‘Health Insurance Cross Sell Prediction’ dataset to perform machine learning task, were to get insights from the independent and dependent variable of a dataset. We’ve all record and data with different Age, Driving License, Region Code, Previously Insured, Vehicle Age, Vehicle Damage, Annual Premium, Policy Sales Channel, Vintage, Response (Target variable – 1 and 0). Providing specific data analysis and prediction to done with this data.

hello-world-docker-action

hotel-booking-analysis

The hotel booking analysis problem has divide into four major parts:- Analysis based on Bookings, Analysis based on Cancellation, General Analysis and Business Perspective.

large-files-and-memory-issues

mercury

Convert Python notebook to web app and share with non-technical users

mlflow-example

An example MLflow project

nikunjsonule

My personal repository

packaging_tutorial

predict-the-domestic-market-contract-blow-molding-low-price.

python-basic-questions

Python Basic (Part -I) - Exercises, Practice, Solution

python-code-challenge

rest-api-microservice-docker

samplemod