Solving Sequence Problems with LSTM in Keras: Part 2

This is the second and final part of the two-part series of articles on solving sequence problems with LSTMs. In the part 1 of the series, I explained how to solve one-to-one and many-to-one sequence problems using LSTM. In this part, you will see how to solve one-to-many and many-to-many sequence problems via LSTM in Keras. Image captioning is a classic example of one-to-many sequence problems where you have a single image as input and you have to predict the […]

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Analyzing API Data with MongoDB, Seaborn, and Matplotlib

Introduction A commonly requested skill for software development positions is experience with NoSQL databases, including MongoDB. This tutorial will explore collecting data using an API, storing it in a MongoDB database, and doing some analysis of the data. However, before jumping into the code let’s take a moment to go over MongoDB and APIs, to make sure we understand how we’ll be dealing with the data we’re collecting. MongoDB and NoSQL MongoDB is a form of NoSQL database, enabling the […]

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Python for NLP: Deep Learning Text Generation with Keras

This is the 21st article in my series of articles on Python for NLP. In the previous article, I explained how to use Facebook’s FastText library for finding semantic similarity and to perform text classification. In this article, you will see how to generate text via deep learning technique in Python using the Keras library. Text generation is one of the state-of-the-art applications of NLP. Deep learning techniques are being used for a variety of text generation tasks such as […]

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File Management with AWS S3, Python, and Flask

Introduction One of the key driving factors to technology growth is data. Data has become more important and crucial in the tools being built as technology advances. It has become the driving factor to technology growth, how to collect, store, secure, and distribute data. This data growth has led to an increase in the utilization of cloud architecture to store and manage data while minimizing the hassle required to maintain consistency and accuracy. As consumers of technology, we are generating […]

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Solving Systems of Linear Equations with Python’s Numpy

The Numpy library can be used to perform a variety of mathematical/scientific operations such as matrix cross and dot products, finding sine and cosine values, Fourier transform and shape manipulation, etc. The word Numpy is short-hand notation for “Numerical Python”. In this article, you will see how to solve a system of linear equations using Python’s Numpy library. What is a System of Linear Equations? Wikipedia defines a system of linear equations as: In mathematics, a system of linear equations […]

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Getting Started with Python PyAutoGUI

Introduction In this tutorial, we’re going to learn how to use pyautogui library in Python 3. The PyAutoGUI library provides cross-platform support for managing mouse and keyboard operations through code to enable automation of tasks. The pyautogui library is also available for Python 2; however, we will be using Python 3 throughout the course of this tutorial. A tool like this has many applications, a few of which include taking screenshots, automating GUI testing (like Selenium), automating tasks that can […]

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Python for NLP: Neural Machine Translation with Seq2Seq in Keras

This is the 22nd article in my series of articles on Python for NLP. In one of my previous articles on solving sequence problems with Keras, I explained how to solve many to many sequence problems where both inputs and outputs are divided over multiple time-steps. The seq2seq architecture is a type of many-to-many sequence modeling, and is commonly used for a variety of tasks such as Text-Summarization, chatbot development, conversational modeling, and neural machine translation, etc. In this article, […]

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Autoencoders for Image Reconstruction in Python and Keras

Introduction Nowadays, we have huge amounts of data in almost every application we use – listening to music on Spotify, browsing friend’s images on Instagram, or maybe watching an new trailer on YouTube. There is always data being transmitted from the servers to you. This wouldn’t be a problem for a single user. But imagine handling thousands, if not millions, of requests with large data at the same time. These streams of data have to be reduced somehow in order […]

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Uploading Files to AWS S3 with Python and Django

Introduction In the quest to build more interactive websites, we don’t only relay information to users but also allow them to upload data of their own. This opens up more opportunities and more ways that our websites can serve the end-users. By allowing users to upload files, we can allow them to share photographs, videos, or music with others or back them up for safekeeping. We can also provide the functionality to manage files and convert them into other formats […]

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Introduction to PyTorch for Classification

PyTorch and TensorFlow libraries are two of the most commonly used Python libraries for deep learning. PyTorch is developed by Facebook, while TensorFlow is a Google project. In this article, you will see how the PyTorch library can be used to solve classification problems. Classification problems belong to the category of machine learning problems where given a set of features, the task is to predict a discrete value. Predicting whether a tumour is cancerous or not, or whether a student […]

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