Recurrent neural networks are a type of neural network where the outputs from previous time steps are fed as input to the current time step. This creates a network graph or circuit diagram with cycles, which can make it difficult to understand how information moves through the…
I ended my last post by saying that I might write a follow-up post on current work that seems to exhibit progress toward natural language understanding. I am going to discuss a couple sampled pap…
Discover topics like sorting, visualization, rainbow, algorithms, satisfying, and the magic of the internet at Imgur, a community powered entertainment destination. Lift your spirits with funny jokes, trending memes, entertaining gifs, inspiring stories, viral videos, and so…
I’m going to describe a way to put together a world-class continuous deployment infrastructure for your side-project without spending any money. With continuous deployment every code commit is tested against …
Scientists, educators and engineers not only use programming languages to build software systems, but also in interactive workflows, using…
Using Machine Learning to understand and leverage text.
Most of us last saw calculus in school, but derivatives are a critical part of machine learning, particularly deep neural networks, which are trained by optimizing a loss function. This article is an attempt to explain all the matrix calculus you need in order to understand the…
Engineering at Forward | UCLA CS '19
Engineering at Forward | UCLA CS '19
NLP Concepts with spaCy. Code examples released under CC0 https://creativecommons.org/choose/zero/, other text released under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ · GitHub
Quantized word vectors that take 8x-16x less space than regular word vectors - agnusmaximus/Word2Bits
Tensorflow (Python API) implementation of Deep Photo Style Transfer - LouieYang/deep-photo-styletransfer-tf
We present Deep Voice 3, a fully-convolutional attention-based neural text-to-speech (TTS) system. Deep Voice 3 matches state-of-the-art neural speech synthesis systems in naturalness while...
This post presents 5 practical resources for getting a start in natural language processing, covering a wide array of topics and approaches.
An open source framework for configuring, building, deploying and maintaining deep learning models in Python.
We ask marketers to define AI, one of the industry's most prevalent buzzwords.
Generative adversarial networks (GANs) are a class of neural networks that are used in unsupervised machine learning. They help to solve such tasks as image generation from descriptions, getting high resolution images from low resolution ones, predicting which drug could treat a…
Build an 'auto-tagging' image search service using Algolia and Google Cloud's Vision API
Through a human’s eyes, the world is much more than just the images reflected in our corneas. For example, when we look at a building and admire the intricacies of its design, we can appreciate...
In this guide I will show you how to use Firebase, React, and Ant Design as building blocks to build functional, high-fidelity web applications. To illustrate this, we’ll go through an example of building a todo list app. These days, there are so many tools available for web…
Expero's cross-functional teams offer deep expertise in custom software development, product design and technology to solve complex issues and drive innovation.
In this tutorial I demonstrate how to apply object detection with deep learning and OpenCV + Python to real-time video streams and video files.
Opinionated Code Formatter
PyTorch has emerged as a major contender in the race to be the king of deep learning frameworks. What makes it really luring is it’s dynamic computation graph paradigm.
Since writing this post back in 2018, I have extended this to a 4-part series on causal inference: * ➡️️ Part 1: Intro to causal inference and do-calculus [https://www.inference.vc/untitled] * Part 2: Illustrating Interventions with a Toy Example…
Introduction of a new feature-rich golang Jupyter kernel
NLTK 3.3 has been released NLTK 3.3 includes the following: Support Python 3.6 New interface to CoreNLP Support synset retrieval by sense key Minor…
This is an introduction to PyTorch's Tensor class, which is reasonably analogous to Numpy's ndarray, and which forms the basis for building neural networks in PyTorch.
Learn basic and advanced concepts of TensorFlow such as eager execution, Keras high-level APIs and flexible model building.
Master programming by recreating your favorite technologies from scratch. - codecrafters-io/build-your-own-x
Dynamic properties provide opportunities for new creative ideas, but also the potential to add complexity to CSS. Custom properties have a huge potential to change how we write and structure CSS and to a lesser extent, how we use JavaScript to interact with UI components. To get…
Cucumber for Ruby. It's amazing!
Cucumber - Ruby Testing - Ruby language has the following advantages ?
A visual guide to Connectionist Temporal Classification, an algorithm used to train deep neural networks in speech recognition, handwriting recognition and other sequence problems.
A visual approach to understanding resolution based on MTF (modulation transfer function) curves.
Sammy Gelfand is the numbers guy behind the Golden State Warriors’ success. Some pretty good players help, too.
When it comes to performance, what works in the browser doesn’t necessarily suit Node.js. So, how do we make sure a Node.js implementation is fast and fit for purpose? Node is a very versatile platform, but one of the predominant applications is creating networked processes. In…
Building a product that connects to multiple third-party products is a common approach — an annotated twitter thread exploring strategic…
Learn how the world's fastest growing companies have hacked their way to success with innovative products, viral promotions and ingenious marketing campaigns. [6500 words]