Python for NLP: Word Embeddings for Deep Learning in Keras

This is the 16th article in my series of articles on Python for NLP. In my previous article I explained how N-Grams technique can be used to develop a simple automatic text filler in Python. N-Gram model is basically a way to convert text data into numeric form so that it can be used by statisitcal algorithms. Before N-Grams, I explained the bag of words and TF-IDF approaches, which can also be used to generate numeric feature vectors from text […]

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Creating Python GUI Applications with wxPython

Introduction In this tutorial, we’re going to learn how to use wxPython library for developing Graphical User Interfaces (GUI) for desktop applications in Python. GUI is the part of your application which allows the user to interact with your application without having to type in commands, they can do pretty much everything with a click of the mouse. Some of the popular Python alternatives for developing a GUI include Tkinter, and pyqt. However, in this tutorial, we will learn about […]

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Serverless Python Application Development with AWS Chalice

Introduction In software development, we are constantly building solutions for end-users that solve a particular problem or ease/automate a certain process. Therefore, designing and building the software is not the only part of the process, as we have to make the software available to the intended users. For web-based applications, deployment is a very important aspect and part of the process since the application not only needs to work, but also needs to work for many users concurrently and be […]

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Python for NLP: Movie Sentiment Analysis using Deep Learning in Keras

This is the 17th article in my series of articles on Python for NLP. In the last article, we started our discussion about deep learning for natural language processing. The previous article was focused primarily towards word embeddings, where we saw how the word embeddings can be used to convert text to a corresponding dense vector, which can be subsequently used as input to any deep learning model. We perform basic classification task using word embeddings. We used custom dataset […]

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Image Classification with Transfer Learning and PyTorch

Introduction Transfer learning is a powerful technique for training deep neural networks that allows one to take knowledge learned about one deep learning problem and apply it to a different, yet similar learning problem. Using transfer learning can dramatically speed up the rate of deployment for an app you are designing, making both the training and implementation of your deep neural network simpler and easier. In this article we’ll go over the theory behind transfer learning and see how to […]

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Rounding Numbers in Python

Using a computer in order to do rather complex Math is one of the reasons this machine was originally developed. As long as integer numbers and additions, subtractions, and multiplications are exclusively involved in the calculations, everything is fine. As soon as floating point numbers or fractions, as well as divisions, come into play it enormously complicates the whole matter. As a regular user, we are not fully aware of these issues that happen behind the scenes and may end […]

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Python Docstrings

As already pointed out in a previous article titled Commenting Python Code you have learned that documentation is an essential, and a continuous step in the process of software development. The article mentioned above briefly introduced the concept of docstrings which is a way to create documentation for your Python code from within the code. This in-code documentation works for modules, classes, methods, and functions, and it is the preferred way to document all Python code. There is a lot […]

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Using Django Signals to Simplify and Decouple Code

Introduction Systems are getting more complex as time goes by and this warrants the need to decouple systems more. A decoupled system is easier to build, extend, and maintain in the long run since not only does decoupling reduce the complexity of the system, each part of the system can be managed individually. Fault tolerance has also enhanced since, in a decoupled system, a failing component does not drag down the entire system with it. Django is a powerful open-source […]

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Basics of Memory Management in Python

Introduction Memory management is the process of efficiently allocating, de-allocating, and coordinating memory so that all the different processes run smoothly and can optimally access different system resources. Memory management also involves cleaning memory of objects that are no longer being accessed. In Python, the memory manager is responsible for these kinds of tasks by periodically running to clean up, allocate, and manage the memory. Unlike C, Java, and other programming languages, Python manages objects by using reference counting. This […]

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Debugging Python Applications with the PDB Module

Introduction In this tutorial, we are going to learn how to use Python’s PDB module for debugging Python applications. Debugging refers to the process of removing software and hardware errors from a software application. PDB stands for “Python Debugger”, and is a built-in interactive source code debugger with a wide range of features, like pausing a program, viewing variable values at specific instances, changing those values, etc. In this article, we will be covering the most commonly used functionalities of […]

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