A Brief Article on the History, Differences and Use-Cases of each Rooting Approach
Stemming and Lemmatization are text preprocessing methods within the field of NLP that are used to standardize text, words, and documents for further analysis. Both in stemming and in lemmatization, we attempt to reduce a given word to its “root”. The root word is called a “stem” in the stemming process, and it is called a “lemma” in the lemmatization process.
You may, for instance, want your program to acknowledge that the words “shoot” and “shot” are just different tenses of the same verb. …
Deep learning can be an intimidating subject for any new, aspiring data scientist. Luckily, there are some great libraries that help to demystify the world of neural networks and deep learning.
In this article I will be providing an initial overview of the Keras library. I will also provide some basic demonstrations of the speed and power Keras provides its users with respect to deep learning classification.
After reading through (don’t worry, it should only take about 5 minutes) you will have the basic skills and know-how to begin using Keras yourself!
Created and maintained by Google, TensorFlow is an open source library for numerical computation and large-scale machine learning. It was released as open-source software in November 2015, and has since become one of the most popular frameworks for machine learning and deep learning projects.
It uses Python to provide a convenient front-end API for building applications with the framework, while executing those applications in C++.
TensorFlow can train and run deep neural networks for:
A brief discussion on the history and current uses of CAPTCHA
Have you ever stopped to wonder why, when attempting to enter a website, you are suddenly asked to prove your own humanity? And furthermore, have you ever reflected on how these websites will attempt to assess you?
If I — a human — were to assess whether or not you were human, I would probably not ask you to transcribe some of my poorly written cursive. Neither would I ask you to select pictures of cars from an assortment of random images. …