Data based Neural networks accuracy is poor

**MLNewbie** · January 28, 2018, 11:47pm

Hi Friends - I’m wondering how to go about creating neural networks for data based problems. I was trying my hands on with a house price prediction problem. I tried a simple, as well as few layered networks(took example from a kaggle competition kernel), but the training accuracy never gets past 1%. So I think am doing something terribly wrong. I would like to get some suggestions on how to approach these kind of problems.

Here is the github link for the notebook and data. - https://github.com/iosnewbie2016/housepricepredict

Can someone pls guide me on this. Help is much appreciated.

Thanks.

**jeremy** · January 28, 2018, 11:49pm

Try watching video 4 of the new course and following the approach there.

**MLNewbie** · January 29, 2018, 12:04am

Thanks Jeremy.

**ecdrid** · January 29, 2018, 6:52am

@MLNewbie
I don’t think so…
Here’s my and I am happy with my position on LB…

Let me know if you ran into some trouble on this nbs
(hadn’t made much changes to the reference notebooks though)

github.com

AdityaSoni19031997/Machine-Learning/blob/master/Classifying_datasets/Houses/house_kaggle.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "## Necessary Imports\n",

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**Brintiawebinar** · April 10, 2019, 1:33pm

I just saw this free webinar on Nueral networks and thought it might be useful https://www.brintia.com/webinar-the-keys-to-understanding-neural-networks/