‫So now let's start building an image classifiet in Python.
‫But before that, we need to install and import tensor flow and keras,
‫Then we will import the dataset that we are going to use for this image classifier.
‫And then we will normalize our data.
‫And after that, we will start creating neural network with keras.
‫First, we are importing some basic libraries.
‫We are importing numpy.
‫We are importing pandas and we are importing matplot to visualise our image data set. Now before importing
‫tensorflow.
‫You need to install it.
‫To install, you have to go to your command prompt.
‫So first press windows R it will open the dialog box.
‫Then you have to write cmd , cmd stands for command prompt and then click on OK.
‫Here, write
‫Conda install tensflow
‫Then press enter.
‫It may take some time.
‫In my system, the tensorflow is already installed.
‫Then we need to upgrade the tense flow version to 2.0.
‫Since we will be using tensorflow 2.0 for this course.
‫To upgrade it, you have to write this statement.
‫Pip space install, then upgrade tensorflow equal to two point zero.
‫So download
‫This jupyter note book, copy this command and run it in your
‫Command prompt.
‫If you are facing any error, then you first have to install the PIP.
‫You can use this command to install PIP.
‫And if you're still facing some error, then you have to correct your environment variables.
‫You'll find a separate.
‫Video about how to setup your environment variables in the appendix section of this course.
‫So remember, first, run this command conda install tensflow, then install Pip and then run
‫this command to upgrade your of flow to 2.0 plus version.
‫Now, if you have successfully installed tensorflow
‫We need to import it.
‫We're importing tens of flow as tf and we're also importing keras from and tensorflow
‫Now you can check the version of your installed tensorflow using this command.
‫So for keras, you can write keras dot double underscore version.
‫Double underscore.
‫Just run this.
‫And you can find that the keras that is installed in my system is two point two point four.
‫To check the version of tensorflow.
‫We can call the same attribute.
‫So tf. double underscore version double under score.
‫You can see that the version is two point zero point zero.
‫So just make sure that the installed version on your P.C. is greater than 2.0.
‫In the next video, we will import the dataset that we are going to use for our first classification
‫example.