Seaborn is one of the go-to tools for statistical data visualization in python. It has been actively developed since 2012 and in July 2018, the author released version 0.9. This version of Seaborn has several new plotting features, API changes and documentation updates which combine to enhance an already great library. This article will walk through a few of the highlights and show how to use the new scatter and line plot functions for quickly creating very useful visualizations of data.

In this project I am Cleaning, Analysing and creating Visualizations to make data easily accessible of ease use.

The "House Price Prediction" project focuses on predicting housing prices using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, and XGBoost, this project provides an end-to-end solution for accurate price estimation.

Kickstart AI through Machine Learning and Deep Learning Projects (20+)

Data visualization is the visual presentation of data or information. The goal of data visualization is to communicate data or information clearly and effectively to readers. Typically, data is visualized in the form of a chart, infographic, diagram or map.

A repository of resources for understanding the concepts of machine learning/deep learning. 

This repo consists of all courses of IBM - Data Science Professional Certificate, providing with techniques covering a wide array of data science topics including open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets.

Samples of EDA(Exploratory Data Analysis) with python pandas

Jupyter notebooks for generating anomaly detection plots used in the Positive Hack Days talk

Implementation of Decision Tree Classifier, Esemble Learning, Association Rule Mining and Clustering models(Kmodes & Kprototypes) for Customer attrition analysis of telecommunication company to identify the cause and conditions of the churn.

A Perfect Repository For Data Anaysis with Jupyter Notebook.:chart_with_upwards_trend::chart_with_downwards_trend:

Exploratory Data Analysis and Price Predictions for Avocado Dataset based on Machine Learning

Welcome to "Data Slices", where imagination and information converge, inviting you to see the world through a new lens of data-driven artistry.

Data Visualization in Python using Matplotlib, Seaborn and Plotly Express

Fbref is a popular football stats/metrics site which collections information from Ted Knutson's StatsBomb. You can save this data in a csv or excel format. This is a Python module which collects any raw csv file from Fbref and plot the data based on whichever two axes you want it to. You can also scrape data from whichever Fbref page you wish to.

A basic extension library for creating tree dot plots, strip plots or dot charts w/ matplotlib or seaborn in Python

This project understands how the student's performance (test scores) is affected by other variables such as Gender, Ethnicity, Parental level of education, Lunch and Test preparation course

Data Visualization With Seaborn

This repository contains the collection of Python and Javascript (Observable Notebook) projects made for the DTU Data Science course 02806: Social Data Analysis and Visualizations

機器學習基礎教學

The Detailed Analysis of Indian Airlines.

The most famous competition over the kaggle .

Build MAXELLA App to recommend Movies using TensorFlow Recommenders (TFRS)

This Repository contains the data analysis of Book crossing dataset with a machine learning implementation

A model was built to predict the total insurance claim amount payable by the insurance company using machine learning techniques such as regression in python.

To import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. I will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them.

During this Online Coding Internship, I have worked on projects related to Data Analytics and Machine Learning.

Leave your regressions behind 🙈 and Let's #makeIThappen with Data Science ⚡

Project on Ant Colony Optimization applied to the Flow Shop Problem

Simple yet powerful header-only c++ library for plotting using Python and ZeroMQ