There are 8 repositories under datawrangling topic.
A fluent code explorer for R. 🔍
This project analyzes and visualizes the Used Car Prices from the Automobile dataset in order to predict the most probable car price
Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and suggested a best model to predict the final sale price of a house. Seaborn is used to plot graphs and scikit learn package is used for statistical analysis.
course website for data science tools 1
Python Data Analytics, Machine Learning & Natural Language Processing
Data Science and Artificial Intelligence advanced certification course led by the IIT Madras & Intellipaat
Fundamentals of Quantitative Analysis
This repository is a collection of all the solutions of tasks that were assigned to me during my Data Analytics Virtual Internship Experience Program at Quantium. 💻📚📊
All dataset analyzed during ALX data analyst nanodegree program including project files
A small utility for analyzing data structures (e.g. JSON files)
Scrapers, parsers, data wrangling and utilities for TikTok and YouTube
It includes full exploratory data analysis (EDA) and preprocessing steps before applying machine learning algorithms. The project uses various datasets and covers data wrangling, exploratory data analysis, data visualization, feature engineering
A collection of projects as part of the Python for Data Science program at GreyAtom EduTech Pvt Ltd
This project is part of the IBM Data Science Professional Certificate course. It aims to identify the best classifier to predict whether the first stage of a Falcon9 rocket will land successfully, helping SpaceX minimize costs.
This project aims to predict employee salaries based on their experience. It involves data wrangling, exploratory data analysis, data visualization, and applies linear regression for prediction.
This project aims to predict student grades using various independent features. It involves data wrangling, exploratory data analysis, data visualization, and linear regression. The project uses Python and Jupyter notebooks for implementation.
Udacity Data Analyst Nanodegree
Personal finance database creation, SQL analysis, and Power BI dashboard
Analyze the Olist dataset with ease using Python DataAnalysis class. Fetch, clean, and visualize data on customer cities, payment types, order status, and popular seller cities. Dive into the world of data analysis with SQLite, Pandas, Matplotlib, and Seaborn. Discover insights and trends in the Olist dataset effortlessly.
Performed data visualization using Tableau to analyze my own chess games played on lichess.org. I downloaded data from Lichess, and convert it from PGN format to CSV. Utilized various chartsto communicate insights, user-friendly interface.
This project features a Next Word Prediction Model deployed via a FLASK API, implemented using a Bi-LSTM model with an attention layer.
I have successfully completed a 16-week and 8 end-to-end, applied data science projects of the Applied Data Science Lab module at WorldQuant University. The mini-projects included scientific computing, data wrangling, machine learning and natural language processing with Python.
The purpose of this project was to compare the performance of Pymaceuticals’ drug of interest, Capomulin, against the other treatment regimens.
The dataset you can find in Kaggle
You can find the dataset in kaggle
In this project, we predicted if the Falcon 9 first stage will land successfully by following the data science methodology.
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.
Data visualization with Python
Explore a sophisticated R Shiny app, the "Global Economic Dashboard," analyzing 20 countries' economic data (2012–2022) with advanced 2D/3D visualization and a predictive Regression ML model for Education Expenditure (%GDP). Do check PowerBI Dashboard for the same!
Trabajas como científico/a de datos para Data Insider, un reconocido equipo de asesores financieros con presencia global, y te ha sido solicitado que elabores un informe detallado para entender de manera objetiva el comportamiento de grandes corporaciones a nivel mundial a partir del año 2015.