Some useful examples of Deep Learning (.ipynb)

Notebooks from my blog. meterdatascience.weebly.com

A data-scientific approach to determining which people were most likely to die on the RMS Titanic.

My notebook that a sent to Kaggle Titanic challenge.

If you liked my analysis, pls upvote my notebook!

Neural Network ConsoleでKaggleのタイタニックを学習するサンプルです。前処理(Jupyter Notebook)、学習・モデル構造自動探索(Neural Network Console)、ONNX推論(Jupyter Notebook)を含みます

My attempt at the introduction to machine learning Kaggle competition: "Titanic: Machine Learning from Disaster"

Repository containing the jupyter notebook for generating results out of the competition called Titanic on Kaggle

This repository contains simple usage examples for basic machine learning libraries. These notebooks are tested in Colab.

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.

In this project, we extracted, transformed, loaded and imported the Titanic dataset into Python Jupiter Notebook. Then, we carried out Exploratory Data Analysis (EDA) as well as logistic regression analysis to predict survivals.