Fake News Detection using LSTM in TensorFlow and Python

I will show you how to do fake news detection in TensorFlow and Python using LSTM. LSTM is a deep learning method to train ML model. I will be also using here gensim Python package to generate word2vec matrix. This method is 99% accurate as shown in this video lecture.

#python #tensorflow

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top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

…

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Fake News Detection Project in Python [With Coding]

Ever read a piece of news which just seems bogus? We all encounter such news articles, and instinctively recognise that something doesn’t feel right. Because of so many posts out there, it is nearly impossible to separate the right from the wrong. Here, we are not only talking about spurious claims and the factual points, but rather, the things which look wrong intricately in the language itself.

Did you ever wonder how to develop a fake news detection project? But there is no easy way out to find which news is fake and which is not, especially these days, with the speed of spread of news on social media. Still, some solutions could help out in identifying these wrongdoings.

There are two ways of claiming that some news is fake or not: First, an attack on the factual points. Second, the language. The former can only be done through substantial searches into the internet with automated query systems. It could be an overwhelming task, especially for someone who is just getting started with data science and natural language processing.

The latter is possible through a natural language processing pipeline followed by a machine learning pipeline. It is how we would implement our fake news detection project in Python. It is another one of the problems that are recognized as a machine learning problem posed as a natural language processing problem.

There are many datasets out there for this type of application, but we would be using the one mentioned here. The data contains about 7500+ news feeds with two target labels: fake or real. The dataset also consists of the title of the specific news piece.

The steps in the pipeline for natural language processing would be as follows:

1. Acquiring and loading the data
2. Cleaning the dataset
3. Removing extra symbols
4. Removing punctuations
5. Removing the stopwords
6. Stemming
7. Tokenization
8. Feature extractions
9. TF-IDF vectorizer
10. Counter vectorizer with TF-IDF transformer
11. Machine learning model training and verification

#data science #fake news #fake news detection #fake news detection project #python project #python project ideas

Lambda, Map, Filter functions in python

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

Deep Learning Project : Real Time Object Detection in Python & Opencv

Real Time Object Detection in Python And OpenCV

Github Link: https://github.com/Chando0185/Object_Detection

Blog Link: https://knowledgedoctor37.blogspot.com/#

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#python project #object detection #python opencv #opencv object detection #object detection in python #python opencv for object detection

How To Compare Tesla and Ford Company By Using Magic Methods in Python

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.

1. init

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

2. add

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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