Deep_learning

Introduction

In this project, build a neural network from scratch to carry out a prediction problem on a real dataset! Built a neural network from the ground up. Implemented gradient descent, backpropagation, forwardpropogation and other concepts. by using tools such as Tensorflow, numpy, pandas and jupyter notebook.

The data comes from the UCI Machine Learning Database.

Instructions

Download the project materials from our GitHub repository.

cd into the first-neural-network directory.

Download anaconda or miniconda based on the instructions in the Anaconda lesson.

Create a new conda environment:

conda create --name dlnd python=3

Enter your new environment:

Mac/Linux: >> source activate dlnd Windows: >> activate dlnd

Ensure you have numpy, matplotlib, pandas, and jupyter notebook installed by doing the following:

conda install numpy matplotlib pandas jupyter notebook

Run the following to open up the notebook:

jupyter notebook dlnd-your-first-neural-network.ipynb

Follow the instructions in the notebook will lead you through the project.