In this detailed step-by-step guide, learn what Transfer Learning is and learn how to create a cutting-edge Image Classification model for CIFAR10, with EfficientNet-B0 in Keras and Tensorflow. | Continue reading
In this tutorial, we'll take a look at examples on how to create a PDF invoice in Python using pText - as well as how to embed files and add outlines. | Continue reading
In an earlier article [/levenshtein-distance-and-text-similarity-in-python/] Igave you an introduction into phonetic algorithms, and shows their variety. Inmore detail we had a look at the edit distance, which is also known as the Levenshtein Distance [https://en.wikipedia.org/w … | Continue reading
In an earlier article [/levenshtein-distance-and-text-similarity-in-python/] Igave you an introduction into phonetic algorithms, and shows their variety. Inmore detail we had a look at the edit distance, which is also known as the Levenshtein Distance [https://en.wikipedia.org/w … | Continue reading
IntroductionIt is imperative to carry out server-side validation when building applications- especially client-facing applications. The reason being, one can never rely onthe user’s input alone; as these inputs sometimes contain bogus/malicious data.Client-side validation is a gr … | Continue reading
Introduction JavaScript has come a long way over the years, and we're now at a point where you can write and deploy a web application very easily. Frameworks like Express, Sails, and Meteor have only made this easier. Following most tutorials on the internet means you'll be worki … | Continue reading
Introduction Design principles are generalized pieces of advice or proven good coding practices that are used as rules of thumb when making design choices. They're a similar concept to design patterns, the main difference being that design principles are more abstract and general … | Continue reading
What is VirtualEnv? The virtualenv tool creates an isolated Python environment (in the form of a directory) that is completely separate from the system-wide Python environment. What this really means is that any settings, 3rd-party packages, etc. from the system-wide environment … | Continue reading
Introduction Graphs are a convenient way to store certain types of data. The concept was ported from mathematics and appropriated for the needs of computer science. Due to the fact that many things can be represented as graphs, graph traversal has become a common task, especially … | Continue reading
In this article, you will learn how to perform time series forecasting that is used to solve sequence problems. Time series forecasting refers to the type of problems where we have to predict an outcome based on time dependent inputs. A typical example of time series data is stoc … | Continue reading
Introduction Object detection is a technology that falls under the broader domain of Computer Vision. It deals with identifying and tracking objects present in images and videos. Object detection has multiple applications such as face detection, vehicle detection, pedestrian coun … | Continue reading
This is the 20th article in my series of articles on Python for NLP. In the last few articles, we have been exploring deep learning techniques to perform a variety of machine learning tasks, and you should also be familiar with the concept of word embeddings. Word embeddings is a | Continue reading
Introduction Way back in the late 1920s John Von Neumann established the main problem in game theory that has remained relevant still today: Players s1, s2, ..., sn are playing a given game G. Which moves should player sm play to achieve the best possible outcome? Shortly after, … | Continue reading
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 … | Continue reading
Introduction Collections in Python are containers that are used to store collections of data, for example, list, dict, set, tuple etc. These are built-in collections. Several modules have been developed that provide additional data structures to store collections of data. One suc … | Continue reading
Introduction Genetic algorithms are a part of a family of algorithms for global optimization called Evolutionary Computation, which is comprised of artificial intelligence metaheuristics with randomization inspired by biology. Wow, words can really be arranged in any order! But h … | Continue reading
Introduction Gradient boosting classifiers are a group of machine learning algorithms that combine many weak learning models together to create a strong predictive model. Decision trees are usually used when doing gradient boosting. Gradient boosting models are becoming popular b … | Continue reading
This is the 15th article in my series of articles on Python for NLP. In my previous article, I explained how to implement TF-IDF approach from scratch in Python. Before that we studied, how to implement bag of words approach from scratch in Python. Today, we will study the N-Gram … | Continue reading
This is the 14th article in my series of articles on Python for NLP. In my previous article, I explained how to convert sentences into numeric vectors using the bag of words approach. To get a better understanding of the bag of words approach, we implemented the technique in Pyth … | Continue reading
Introduction Are you interested in using a neural network to generate text? TensorFlow and Keras can be used for some amazing applications of natural language processing techniques, including the generation of text. In this tutorial, we'll cover the theory behind text generation … | Continue reading
Introduction Phaser 3 enables us to quickly create games in our browser with JavaScript. Some of our favorite 2D games are platformers - think of games like Mario, Sonic, Super Meat Boy, or Cuphead. Tiled is a 2D map editor that's used to create game worlds. We'll explore how to | Continue reading
Introduction In this tutorial, we are going to learn how to use OpenCV library in Python. OpenCV is an open source library which is supported by multiple platforms including Windows, Linux, and MacOS, and is available for use in multiple other languages as well; however, it is mo … | Continue reading
Introduction Linear regression is one of the most commonly used algorithms in machine learning. You'll want to get familiar with linear regression because you'll need to use it if you're trying to measure the relationship between two or more continuous values. A deep dive into t … | Continue reading
Introduction Game development is a unique branch of software development that can be as rewarding as it is complex. When thinking of creating games, we usually think of an application to install and play on our computers or consoles. The HTML5 spec introduced many APIs to enable … | Continue reading
Introduction When designing a completely new algorithm, a very thorough analysis of its correctness and efficiency is needed. The last thing you would want is your solution not being adequate for a problem it was designed to solve in the first place. In this article we will be ta … | Continue reading
Introduction In this article, we will be using the Wikipedia API to retrieve data from Wikipedia. Data scraping has seen a rapid surge owing to the increasing use of data analytics and machine learning tools. The Internet is the single largest source of information, and therefore … | Continue reading
Introduction One of the most common utilizations of Tensorflow and Keras is the recognition/classification of images. If you want to learn how to use Keras to classify or recognize images, this article will teach you how. Definitions If you aren't clear on the basic concepts behi … | Continue reading
Introduction In this tutorial I will be providing a general understanding of why celery message queue's are valuable along with how to utilize celery in conjunction with Redis in a Django application. To demonstrate implementation specifics I will build a minimalistic image proce … | Continue reading
The performance of a Java program and the proper use of resources are often depend on a collection a developer chose for storing data. Hence, it is very important to understand the difference between the implementations. That's why questions related to collections are in the top … | Continue reading
Python 3's asyncio module provides fundamental tools for implementing asynchronous I/O in Python. It was introduced in Python 3.4, and with each subsequent minor release, the module has evolved significantly. This tutorial contains a general overview of the asynchronous paradigm, … | Continue reading
This is my 11th article in the series of articles on Python for NLP and 2nd article on the Gensim library in this series. In a previous article, I provided a brief introduction to Python's Gensim library. I explained how we can create dictionaries that map words to their correspo … | Continue reading
Introduction GraphQL is a graph-oriented query language written by Facebook. In contrast to REST APIs, GraphQL introduces features that make API development more efficient and in tune with database models. GraphQL Features Unlike REST, there is only one endpoint where all request … | Continue reading
Introduction Reinforcement Learning is definitely one of the most active and stimulating areas of research in AI. The interest in this field grew exponentially over the last couple of years, following great (and greatly publicized) advances, such as DeepMind's AlphaGo beating the … | Continue reading
This is the 10th article in my series of articles on Python for NLP. In my previous article, I explained how the StanfordCoreNLP library can be used to perform different NLP tasks. In this article, we will explore the Gensim library, which is another extremely useful NLP library … | Continue reading
Introduction Good software is tested software. Testing our code can help us catch bugs or unwanted behavior. Test Driven Development (TDD) is a software development practice that requires us to incrementally write tests for features we want to add. It leverages automated testing … | Continue reading
This is the ninth article in my series of articles on Python for NLP. In the previous article, we saw how Python's Pattern library can be used to perform a variety of NLP tasks ranging from tokenization to POS tagging, and text classification to sentiment analysis. Before that we … | Continue reading
Introduction The first thing we have to understand while dealing with constraint programming is that the way of thinking is very different from our usual way of thinking when we sit down to write code. Constraint programming is an example of the declarative programming paradigm, … | Continue reading
We will optimize common patterns and procedures in Python programming in an effort to boost the performance and enhance the utilization of the available computing resources. | Continue reading
Introduction Dynamic Programming is typically used to optimize recursive algorithms, as they tend to scale exponentially. The main idea is to break down complex problems (with many recursive calls) into smaller subproblems and then save them into memory so that we don't have to r … | Continue reading
Introduction With the increase in the number of the cores available in the processors nowadays, coupled with the ever increasing need to achieve more throughput, multi-threading APIs are getting quite popular. Java provides its own multi-threading framework called the Executor Fr … | Continue reading
This is the eighth article in my series of articles on Python for NLP. In my previous article, I explained how Python's TextBlob library can be used to perform a variety of NLP tasks ranging from tokenization to POS tagging, and text classification to sentiment analysis. In this … | Continue reading
The PDF Document Format Today, the Portable Document Format (PDF) belongs to the most commonly used data formats. In 1990, the structure of a PDF document was defined by Adobe. The idea behind the PDF format is that transmitted data/documents look exactly the same for both partie … | Continue reading
What is Docker? Docker is a technology that allows you to create and run containers for your applications. Containers are isolated environments that run an application and include its dependencies. They are typically minimal, including just what you need to get your app running a … | Continue reading
Introduction This is the seventh article in my series of articles on Python for NLP. In my previous article, I explained how to perform topic modeling using Latent Dirichlet Allocation and Non-Negative Matrix factorization. We used the Scikit-Learn library to perform topic modeli … | Continue reading
This article applies to sites created with the Spring Boot framework. We will be discussing the following four methods to add additional layers of security to Spring Boot apps: Preventing SQL Injection using Parameterized Queries URL Parameter Input Validation Form Field Input Va … | Continue reading
This is the fifth article in the series of articles on NLP for Python. In my previous article, I explained how Python's spaCy library can be used to perform parts of speech tagging and named entity recognition. In this article, I will demonstrate how to do sentiment analysis usin … | Continue reading
This article applies to sites created with the Spring Boot framework, using Apache Maven as the build tool. In order to demonstrate how profiles work, we'll visit an example using Google Analytics and Google Tag Manager for tracking site metrics. I use this method for my website, … | Continue reading
This article applies to sites created with the Spring Boot framework, using Apache Maven as the build tool. In order to demonstrate how profiles work, we'll visit an example using Google Analytics and Google Tag Manager for tracking site metrics. I use this method for my website, … | Continue reading