This is a new format in whihc I am going to try myself in the next couple of weeks - paper summaryes. This is a paper by Xiang Zhang and Yann LeCun from NYU. Be sure to read the full paper after reading this summary. You can find the paper here. In this paper, they … Continue reading Text Understanding from Scratch: Paper Summary

# Tag: Deep Learning

# Mathematical Basics Of Gradient Descent

Gradient descent is the backbone of a lot of machine learning algorithms, deep learning included. It is used only during the training, and it is the most computationally expensive part of machine learning. Gradient descent is a very complicated mathematical topic which I cannot explain in its entirety in a single blog post. However, I … Continue reading Mathematical Basics Of Gradient Descent

# Neural Network Output Units

The primary function of a feedfoward neural network is to create a prediction of some sorts. The most popular task that is handled by a feedfoward neural network is classification or categorization. Classification is a task where a program is handed some sort of data, and the program classifies the data as something. One popular … Continue reading Neural Network Output Units

# Neural Style Transfer In Keras

This has got to be one of the coolest implementations of machine learning. If you don't know what neural style transfer is, it's basically taking a content image, like a photograph that you took of you and your family, and a style image, most of the time you would choose a famous painting with a … Continue reading Neural Style Transfer In Keras

# Rewriting Siraj Raval’s Game of Thrones Word Vectors Using Tensorflow

Siraj Raval's video on how to make word vectors out of five A Song Of Ice And Fire books is a helpful demonstration of word embeddings, but not so helpful as a tutorial because he uses a bunch of smaller libraries which enable you to do the training of the model in just a couple … Continue reading Rewriting Siraj Raval’s Game of Thrones Word Vectors Using Tensorflow

# Activation functions explained

I love this kind of featured images. It makes people think that you are so smart and that you've figured out life. They're hilarious. It it makes the topic of the post seem like it's really deep, pun intended. If you've worked with neural networks even a little bit, you've probably come across the term activation function. … Continue reading Activation functions explained

# What Is Dropout? – Deep Learning

Overfitting can be a serious problem in deep learning. Dropout is a technique developed to solve this exact problem. It is one of the biggest advancements in deep learning to come out in the last few years. What is dropout? Dropout is a technique for addressing the overfitting problem. The idea is to randomly drop … Continue reading What Is Dropout? – Deep Learning

# How I Plan On Learning Deep Learning

Learning any technology can be tricky. Especially if it's your first one. Luckily, it's not for me. I do already have some programming experience. I have some experience with Java and Kotlin. I wrote some Android apps. Android is not really for me. I do not like anything that requires you to do some front … Continue reading How I Plan On Learning Deep Learning