Build Your First Text Classification model using PyTorch

Overview Learn how to perform text classification using PyTorch Grasp the importance of Pack Padding feature Understand the key points involved while solving text classification Introduction I always turn to State of the Art architectures to make my first submission in data science hackathons. Implementing the State of the Art architectures has become quite easy thanks to deep learning frameworks such as PyTorch, Keras, and TensorFlow. These frameworks provide an easy way to implement complex model architectures and algorithms with […]

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Top 10 Applications of Natural Language Processing (NLP)

Introduction Natural Language Processing is among the hottest topic in the field of data science. Companies are putting tons of money into research in this field. Everyone is trying to understand Natural Language Processing and its applications to make a career around it. Every business out there wants to integrate it into their business somehow. Do you know why?   Because just in a few years’ time span, natural language processing has evolved into something so powerful and impactful, which […]

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Machine Learning in Cyber Security — Malicious Software Installation

Introduction Monitoring of user activities performed by local administrators is always a challenge for SOC analysts and security professionals. Most of the security framework will recommend the implementation of a whitelist mechanism. However, the real world is often not ideal. You will always have different developers or users having local administrator rights to bypass controls specified. Is there a way to monitor the local administrator activities?

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Save Plot as Image with Matplotlib

Introduction Matplotlib is one of the most widely used data visualization libraries in Python. It’s common to share Matplotlib plots and visualizations with others. In this article, we’ll take a look at how to save a plot/graph as an image file using Matplotlib. Creating a Plot Let’s first create a simple plot: import matplotlib.pyplot as plt import numpy as np x = np.arange(0, 10, 0.1) y = np.sin(x) plt.plot(x, y) plt.show() Here, we’ve plotted a sine function, starting at 0 […]

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Machine Translation Weekly 44: Tangled up in BLEU (and not blue)

For quite a while, machine translation is approached as a behaviorist simulation. Don’t you know what a good translation is? It does not matter, you can just simulate what humans do. Don’t you know how to measure if something is a good translation? It does not matter, you can simulate what humans do again. Things seem easy. We learn how to translate from tons of training data that were translated by humans. When we want to measure how well the […]

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Machine Translation Weekly 45: Deep Encoder, Shallow Decoder, and the Fall of Non-autoregressive models

Researchers concerned with machine translation speed invented several methods that are supposed to significantly speed up the translation while maintaining as much as possible from the translation quality of the state-of-the-art models. The methods are usually based on generating as many words as possible in parallel. State-of-the-art models do not generate in parallel, they are autoregressive: it means that they generate words one by one and condition the decisions about the next words on the previously generated words. On the […]

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Python with Pandas: DataFrame Tutorial with Examples

Introduction Pandas is an open-source Python library for data analysis. It is designed for efficient and intuitive handling and processing of structured data. The two main data structures in Pandas are Series and DataFrame. Series are essentially one-dimensional labeled arrays of any type of data, while DataFrames are two-dimensional, with potentially heterogenous data types, labeled arrays of any type of data. Heterogenous means that not all “rows” need to be of equal size. In this article we will go through […]

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Remove Element from an Array in Python

Introduction This tutorial will go through some common ways for removing elements from Python arrays. Here’s a list of all the techniques and methods we’ll cover in this article: Arrays in Python Arrays and lists are not the same thing in Python. Although lists are more commonly used than arrays, the latter still have their use cases. The main difference between the two is that lists can be used to store arbitrary values. They are also heterogeneous which means they […]

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Guide to String Interning in Python

Introduction One of the first things you encounter while learning the basics of programming is the concept of strings. Similar to various programming languages, Python strings are arrays of bytes representing Unicode characters – an array or sequence of characters. Python, unlike many programming languages, doesn’t have a distinct character datatype, and characters are considered strings of length 1. You can define a string using single or double quotation marks, for example, a = “Hello World” or a = ‘Hello […]

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Python: Check if Variable is a Number

Introduction In this article, we’ll be going through a few examples of how to check if a variable is a number in Python. Python is dynamically typed. There is no need to declare a variable type, while instantiating it – the interpreter infers the type at runtime: variable = 4 another_variable = ‘hello’ Additionally, a variable can be reassigned to a new type at any given time: # Assign a numeric value variable = 4 # Reassign a string value […]

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