October 30, 2018

192 words 1 min read

llSourcell/How_to_use_Tensorflow_for_classification-LIVE

llSourcell/How_to_use_Tensorflow_for_classification-LIVE

This is the code for the “How to Use Tensorflow for Classification” live session by Siraj Raval on Youtube

repo name llSourcell/How_to_use_Tensorflow_for_classification-LIVE
repo link https://github.com/llSourcell/How_to_use_Tensorflow_for_classification-LIVE
homepage
language Jupyter Notebook
size (curr.) 7 kB
stars (curr.) 75
created 2017-01-25
license

How_to_use_Tensorflow_for_classification-LIVE

This is the code for the “How to Use Tensorflow for Classification” live session by Siraj Raval on Youtube

##Overview

This is the code for this live session by Siraj Raval on Youtube. We’ll build a classifier for houses. The housing data contains features for each house like # of bathrooms, price, and area. We’ll manually add labels to our data (good buy or bad buy) then given a new house, we’ll predict whether or not it’s a good buy or bad buy. We use gradient descent as our optimization strategy and

##Dependencies

Install dependencies using pip Install jupyter notebook using this

##Usage

type juptyer notebook into terminal and a browser window will pop up. Click on demo.ipynb. You can iteratively compile each block of code to see the output results.

##Credits Credits for the code go to jalammar. I’ve merely created a wrapper to get people started.

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