Deep Learning - FloydHub Blog

Tokenizers: How machines read

We will cover often-overlooked concepts vital to NLP, such as Byte Pair Encoding, and discuss how understanding them leads to better models.

Deep Learning

Distilling knowledge from Neural Networks to build smaller and faster models

This article discusses GPT-2 and BERT models, as well using knowledge distillation to create highly accurate models with fewer parameters than their teachers

Deep Learning

Introduction to Adversarial Machine Learning

Machine learning advancements lead to new ways to train models, as well as deceive them. This article discusses ways to train and defend against attacks.

Deep Learning

Training Neural Nets: a Hacker’s Perspective

This deep dive is all about neural networks - training them using best practices, debugging them and maximizing their performance using cutting edge research.

Deep Learning

Attention Mechanism

What is Attention, and why is it used in state-of-the-art models? This article discusses the types of Attention and walks you through their implementations.

Deep Learning

When Not to Choose the Best NLP Model

The world of NLP already contains an assortment of pre-trained models and techniques. This article discusses how to best discern which model will work for your goals.

Deep Learning

N-Shot Learning: Learning More with Less Data

Is it possible to use machine learning with small data? Yes, it is! Here's N-Shot Learning.

Deep Learning

Gated Recurrent Unit (GRU) With PyTorch

The Gated Recurrent Unit (GRU) is the newer version of the more popular LSTM. Let's unveil this network and explore the differences between these 2 siblings.

Deep Learning

Becoming One With the Data

This article discusses effective ways of handling the data in machine learning projects.

Deep Learning

How to plan and execute your ML and DL projects

This article gives the readers a checklist to structure their machine learning (applies to deep ones too) projects in effective ways.

Deep Learning

Generative Adversarial Networks - The Story So Far

Generative adversarial networks (GANs) have been the go-to state of the art algorithm to image generation in the last few years. In this article, you will learn about the most significant breakthroughs in this field, including BigGAN, StyleGAN, and many more.

Deep Learning

Long Short-Term Memory: From Zero to Hero with PyTorch

Long Short-Term Memory (LSTM) Networks have been widely used to solve various sequential tasks. Let's find out how these networks work and how we can implement them.

Deep Learning

Using Deep Learning and TensorFlow Object Detection API for Corrosion Detection and Localization

While computer vision techniques have been used with limited success for detecting corrosion from images, Deep Learning has opened up whole new possibilities

Deep Learning

How to Build OpenAI's GPT-2: "The AI That Was Too Dangerous to Release"

The Key Insights Behind the Greatest Language Model of all Time

Deep Learning

A Beginner’s Guide on Recurrent Neural Networks with PyTorch

Learn the basics of Recurrent Neural Networks and build a simple Language Model with PyTorch

Reinforcement Learning

Meta-Reinforcement Learning

The general trend in machine learning research is to stop fine-tuning models, and instead use a meta-learning algorithm that automatically finds the best architecture and hyperparameters. What about meta-reinforcement learning (meta-RL)? Meta-RL is just meta-learning applied to RL.

Deep Learning

Ten trends in Deep learning NLP

Let's uncover the Top 10 NLP trends of 2019.

Deep Learning

Best Deep Learning Courses: Updated for 2019

The list of the best machine learning & deep learning courses and MOOCs for 2019.

Deep Learning

Best Deep Learning Books: Updated for 2019-2020

The list of the best machine learning & deep learning books for 2019.

Deep Learning

Controlling a 2D Robotic Arm with Deep Reinforcement Learning

Learn how to control a robotic arm using deep reinforcement learning techniques.

Community

Recommending Similar Fashion Images with Deep Learning

Explore how deep learning is changing the fashion industry by training your own visual recommendation model for similar fashion images using TensorFlow and FloydHub

Deep Learning

Building a Toy Self-Driving Car: Part One

Learn the history and technology of autonomous cars in this Part 1 of a series on building a self-driving toy car with Raspberry Pi, Keras, and FloydHub GPUs.

Deep Learning

On Building an Instagram Street Art Dataset and Detection Model

Build your own deep learning dataset and detection model using public Instagram photos of #streetart.

Deep Learning

Haggis, Not Haggis: How to build a haggis detection app with TensorFlow, Keras, and FloydHub for Burns Night

Use TensorFlow to build your own haggis-hunting app for Burns Night! The Scottish quest for the mythical wild haggis just got easier with deep learning.

Deep Learning

Inverting Facial Recognition Models

Can we teach a neural net to convert face embedding vectors back to images?