Some useful examples of Deep Learning (.ipynb)

A classification approach to the machine learning Titanic survival challenge on Kaggle.Data visualisation, data preprocessing and different algorithms are tested and explained in form of Jupyter Notebooks

Jupyter Notebooks com soluções de competições do Kaggle

Spark, Scala, Jupyter Notebook

Notebooks from my blog. meterdatascience.weebly.com

This notebook contains my submission of Titanic submission challenge on Kaggle. Feel free to suggest improvements.

This Python Notebook is a proposal to analyse the Titanic dataset for the Kaggle Competition, using several data science techniques and concepts.

Titanic Survival Prediction: Jupyter Notebook demonstrating Random Forest Classifier for survival prediction on Titanic dataset.

This python notebook contains the linear regression model to predict survivals of the Titanic incident.

This notebook is my first attempt at using PySpark for EDA and Machine Learning models.

A notebook for learning how to handle non-numeric values in Datasets. Quite good 👍

The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of thi…

Exercises and notes completed in the Jupyter Notebook while completing the Udemy course, "Python for Data Analysis and Machine Learning

10 very popular data analysis exercises I have practised with jupyter notebook in my spare time, including Iris flowers, Titanic, K means clustering, linnear regression and logistic regression etc.

This repository contains notebooks that are trained on The Titanic Dataset with ML ensemble methods like Random Forest, Decision trees and XGBoost.

This is a notebook with an exploratory data analysis (EDA) of the Titanic dataset and a machine learning model to predict passenger survival.

This notebook is mostly focused on Beginners Learning for simple machine learning concepts and how to apply them into real world problems.

In this notebook, we will work on the Titanic dataset and use machine learning to create a model that predicts which passengers survived the Titanic shipwreck.

A classification approach to the machine learning Titanic survival challenge on Kaggle.Data visualisation, data preprocessing and different algorithms are tested and explained in form of Jupyter Notebooks

Titanic Survival Prediction Project (93% Accuracy)🛳️ In this notebook, The goal is to correctly predict if someone survived the Titanic shipwreck using different Machine Learning Model & Hyperparameter tunning.