AlmaBetter Capstone Project -Exploratory data analysis (EDA) is used by data scientists to analyze and investigate data sets and summarize their main characteristics, often employing data visualization methods.

AlmaBetter Capstone Project -Machine Learning Project type: Regression. This challenge asks you to build a model that predicts the number of seats that Mobiticket can expect to sell for each ride

AlmaBetter Capstone Project -Exploratory data analysis (EDA) is used by data scientists to analyze and investigate data sets and summarize their main characteristics, often employing data visualization methods.

EDA Capstone Project(Almabetter)

AlmaBetter Capstone Project - Unsupervised ML. Developed a book recommendation system for Amazon customers using memory and model based collaborative filtering by utilizing the description of book consumed and user interests.

AlmaBetter Capstone Project -Machine Learning Project type: Regression. Sales forecasting is an approach retailers use to anticipate future sales by analyzing past sales, identifying trends, and projecting data into the future.

AlmaBetter Capstone Project - Unsupervised ML: Netflix Movies And Tv Shows Clustering This project is a part of the Almabetter Pro Program Curriculum(Full Stack Data Science)

Backend Capstone Project by Almabetter Title : BookMyShow

This repository is made as a part of Frontend Project that was done for, AlmaBetter Fronted Capstone Project. This website is deployed at the link provided below.

Exploratory Data Analysis (EDA) is akin to detective work for data, employing visual tools to uncover patterns and insights. It transforms raw numbers into a compelling narrative, unveiling surprises and secrets within the dataset. Think of it as an investigative journey into the core of your data, revealing hidden truths along the way.