Predicts home prices of Bangalore. Used Flutter, Flask and Jupyter Notebook.

A basic machine learning model built in python jupyter notebook to classify whether a set of tweets into two categories: racist/sexist non-racist/sexist.

This repository shows my Machine learning and Data science learning journey by exploring techniques of data acquisition, cleaning and application of machine learning models

Repository contains notebooks and datasets on no. of flights departures, passengers flew, flights crashed etc.

This notebook involves sentiment analysis on US airline tweets dataset.

Data Cleaning on grades dataset using re and pandas in Jupyter notebook.

Notebook for web scraping and cleaning list of all ISRO missions, satellites, launches ...

This is an example of data cleaning, this project uses Jupiter Notebook and Python

Correlated, cleaned, and visualized data from the movies database using Python3 through Jupyter Notebooks

This notebook contains the EDA, data cleaning, modeling and prediction parts of the "House Price- Advance Regression Techniques" problem from Kaggle.

Performing Data Wrangling (gathering, assessing, cleaning) of WeRateDogs Twitter account & archive using Jupyter Notebook, followed by storing, analyzing and visualizing the wrangled data.

Python / Jupyter Notebook project using Pandas to explore, clean, and investigate school district data trends. Merge, filter, slice, sort, groupby methods used.

Explore comprehensive retail analysis and insights focusing on Marley International Store, powered by data analytics techniques and visualizations using Python, PowerBI and Jupyter Notebooks.

Repository for Raspberry Pi-based object detection with TinyML models like TensorFlow Lite, PyTorch Nano, including data gathering, mAP evaluation, and image data preparation in Jupyter notebooks.

In this notebook, I have done Data Cleaning, Data Wrangling, EDA and Feature Engineering. After that I trained the dataset using Machine Learning Algorithm Random Forest Regressor.

Le projet écrit en Python (notebook jupyter) en deux parties : -Srapper la data à partir du site web : BeautifulSoup, Requests -L'analyse et l'exploitation de la data : Numpy, Pandas,Matplotlib, Seaborn..

This repository is a collection of Python scripts and Jupyter notebooks showcasing various data visualization techniques using the Matplotlib library. It includes examples of different types of graphs and charts, along with explanations of the basic parameters used to customize them.

In this project, I am prominently trying to Analyse the airline data set, First I made a Dashboard in order to have an overview of the data, then I perform Data analysis in Jupyter notebook according to the problem statement and then make a final report.