Task: To predict the percentage of a student based on the number of study hours.
Task: From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.
Automate the process of visualization.
Udacity Data Analyst Nanodegree - Project III
Samples for Azure Databricks Orientation
Plot Matplotlib graphs effortlessly with Django-Pyplot! This Django web application simplifies data visualization, allowing users to create various graphs by entering data without any coding. Enjoy a user-friendly interface, diverse graph types, and seamless integration with Django and Matplotlib.
This repository contains project materials for the Spring 2024 STAT 208 class, specifically for Team 8. All materials are the property of Team 8, University of California, Riverside, A. Gary Anderson School of Management. Thank you for viewing our repository.
Udacity Data Analyst Nanodegree - Project V
This repo consist of projects on: Data Wrangling, Data Visualization and Machine Learning
Data Analyst Nanodegree - Data Visualization
This is a wine dataset containing 1599 rows and 12 columns with factors like alcohol, color, PH, residual sugar, sulfur-dioxide was used to determine the quality of wine varying with color.
we aim to predict trends in the Canadian market basket using sentiment analysis techniques. Sentiment analysis involves analyzing text data to determine the sentiment expressed, whether positive, negative, or neutral.
Data Analyst Nanodegree - Data Visualization project
Statistical exploration, analysis, and visualization of 2012 PISA international education survey
Predicting Sales and Demand of Walmart Data
Perform data analysis of service request (311) calls from New York City. I have utilized data wrangling techniques to understand the pattern in the data and visualize the major types of complaints.
An in-depth book covering essential topics for AI, ML and DL.
Personal financial record keeping and analysis app made in python with statistics and visual summaries.
Python analysis of 2021 LeetCode problems dataset exploring problem attributes like difficulty, acceptance rate, frequency, topics, and company tags. Helps optimize interview prep by identifying problem trends and popular question types.
A selection of data visualisations created during my Data Proccessing course
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