A collection of notebooks for my final year project. The notebooks are used to create a virtual personal trainer to check bicep curls, squats and overhead presses.

Best for beginners | Well explained ML algorithms | organized Notebooks | Case Studies

Análisis de la fuga de empleados de una empresa con implementación de un modelo de Machine Learning para acciones de fidelización.

KNN Classifire by using Python and Jupyter NoteBooks

Scikit-learn (sklearn) projects in form of Jupyter Notebooks

This notebook contains the sentimental analysis of the movie reviews on imdb.

I created this notebook to training my datascience skills, ssing different automatic learning models

Notebook created for a challenge hosted by Summer Analytics by C&A Club IITG.

A bunch of jupyter notebooks containing tensorflow and keras implementation from ANN to GANs to NLP.

A topic-wise collection of mini projects implementing basic machine learning concepts through python. Originally implemented in Google colab notebooks.

This code demonstrates how to use Jupyter Notebooks effectively for deep learning workflows. It covers installing dependencies, running commands, and managing code cells in Google Colab. The notebook serves as a quick-start guide for beginners to set up and execute ML experiments interactively.

This is a very brief notebook on NLP, it contains a "Disaster Analysis" project in which all the possible architectures were shown and described briefly.

This Jupyter Notebooks is an initial study of the application of sklearn neural network MLP Classifier model. The model is applied to dataset MotorPremiums, which is supplied separately in .csv format.

Un projet d'analyse et de reporting sur les films basé sur un dataset Kaggle. Utilisation de Jupyter Notebooks pour explorer les données et visualiser les tendances du cinéma.

DVD Rental Prediction leverages regression models to forecast rental duration, guiding optimal inventory management for DVD rental companies. It combines data visualization, feature engineering, and model evaluation within a Jupyter Notebook to deliver actionable insights.

This repository holds 2 Jupyter notebooks and one csv file on Time Series analysis for the A Yen for the Future exercises. The purpose of this code is to demonstrate understanding of time series work in Python: ARMA, ARIMA and related concepts.

This notebook is a study on the sales of newspapers of a local stand, with intention to predict the newspaper sales performance based on the different features available. For this, 4 sklearn models are applied: Linear Regression, Lasso Regression, Ridge Regression and Elastic Net Regression.

This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this repository is to provide an example of a competitive analysis for those interested in getting into the field of data analytics or using python for Kaggle's Data Science competitions .

This repository is a hub for data science enthusiasts, offering a diverse collection of projects, notebooks, and resources covering topics such as data analysis, machine learning, deep learning, and generative AI. Explore innovative ideas, contribute to cutting-edge research, and enhance your skills in the dynamic field of data science