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Deep Learning

A collection of 45 posts

NLP Datasets: How good is your deep learning model?
Deep Learning

NLP Datasets: How good is your deep learning model?

With the rapid advance in NLP models we have outpaced out ability to measure just how good they are at human level language tasks. We need better NLP datasets now more than ever to both evaluate how good these models are and to be able to tweak them for out own business domains.

  • Cathal Horan
    Cathal Horan
31 min read
Tokenizers: How machines read
NLP

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.

  • Cathal Horan
    Cathal Horan
34 min read
Distilling knowledge from Neural Networks to build smaller and faster 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

  • Alex Amadori
    Alex Amadori
27 min read
Introduction to Adversarial Machine Learning
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.

  • Arunava Chakraborty
    Arunava Chakraborty
35 min read
Training Neural Nets: a Hacker’s Perspective
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.

  • Sayak Paul
    Sayak Paul
26 min read
Attention Mechanism
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.

  • Gabriel Loye
    Gabriel Loye
19 min read
When Not to Choose the Best NLP Model
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.

  • Cathal Horan
    Cathal Horan
15 min read
N-Shot Learning: Learning More with Less Data
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.

  • Heet Sankesara
    Heet Sankesara
15 min read
Gated Recurrent Unit (GRU) With PyTorch
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.

  • Gabriel Loye
    Gabriel Loye
19 min read
Becoming One With the Data
Deep Learning

Becoming One With the Data

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

  • Sayak Paul
    Sayak Paul
29 min read
How to plan and execute your ML and DL 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.

  • Sayak Paul
    Sayak Paul
18 min read
Generative Adversarial Networks - The Story So Far
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.

  • Ajay Uppili Arasanipalai
    Ajay Uppili Arasanipalai
19 min read
Long Short-Term Memory: From Zero to Hero with PyTorch
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.

  • Gabriel Loye
    Gabriel Loye
21 min read
Using Deep Learning and TensorFlow Object Detection API for Corrosion Detection and Localization
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

  • Anirban Konar
    Anirban Konar
22 min read
How to Build OpenAI's GPT-2: "The AI That Was Too Dangerous to Release"
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

  • Ajay Uppili Arasanipalai
    Ajay Uppili Arasanipalai
12 min read
A Beginner’s Guide on Recurrent Neural Networks with PyTorch
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

  • Gabriel Loye
    Gabriel Loye
17 min read
Meta-Reinforcement Learning
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.

  • MichaĂ«l Trazzi
    Michaël Trazzi
20 min read
Ten trends in Deep learning NLP
Deep Learning

Ten trends in Deep learning NLP

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

  • Cathal Horan
    Cathal Horan
21 min read
Best Deep Learning Courses: Updated for 2019
Deep Learning

Best Deep Learning Courses: Updated for 2019

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

  • Alessio Gozzoli
    Alessio Gozzoli
18 min read
Best Deep Learning Books: Updated for 2019-2020
Deep Learning

Best Deep Learning Books: Updated for 2019-2020

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

  • Alessio Gozzoli
    Alessio Gozzoli
15 min read
Controlling a 2D Robotic Arm with Deep Reinforcement Learning
Deep Learning

Controlling a 2D Robotic Arm with Deep Reinforcement Learning

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

  • Mark Saroufim
16 min read
Recommending Similar Fashion Images with Deep Learning
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

  • James Le
    James Le
17 min read
Building a Toy Self-Driving Car: Part One
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.

  • Jaison Saji Chacko
    Jaison Saji Chacko
15 min read
On Building an Instagram Street Art Dataset and Detection Model
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.

  • Leonard Bogdonoff
    Leonard Bogdonoff
17 min read
Haggis, Not Haggis: How to build a haggis detection app with TensorFlow, Keras, and FloydHub for Burns Night
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.

  • Euan Wielewski
    Euan Wielewski
13 min read
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