In the previous post, we saw how we can use TensorFlow on a simple data set. In this example, we are going to use TensorFlow for image classification. The dataset that we are going to use is the MNIST data set that is part of the TensorFlow datasets.
Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map
Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…
You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).
Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.
class AnyClass: def __init__(): print("Init called on its own") obj = AnyClass()
The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.
The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.
Init called on its own
Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,
class AnyClass: def __init__(self, var): self.some_var = var def __add__(self, other_obj): print("Calling the add method") return self.some_var + other_obj.some_var obj1 = AnyClass(5) obj2 = AnyClass(6) obj1 + obj2
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In this tutorial, we will provide you an example of how you can build a powerful neural network model to classify images of **cats **and dogs using transfer learning by considering as base model a pre-trained model trained on ImageNet and then we will train additional new layers for our cats and dogs classification model.
We will work with a sample of 600 images from the Dogs vs Cats dataset, which was used for a 2013 Kaggle competition.
#python #transfer learning #tensorflow #images #transfer learning on images with tensorflow #tensorflow 2
In this tutorial, we will learn how to use
imread() method of OpenCV-Python in detail and different ways to load an image using
Table of Contents
#python modules #opencv-python #python imread() #opencv.imread() #python imread(): different ways to load an image using the opencv.imread() method #load an image