Techniques in Self-Attention Generative Adversarial Networks
Author(s): Sherwin Chen Originally published on Towards AI. Self Attention GAN (SAGAN) U+007C Towards AI Discussion about different approaches of SAGAN like spectral normalization, conditional batch normalization, etc. Image generated by my implementation of SAGAN on celebA dataset after 120k iterations Introduction …
Cross-lingual Language Model
Author(s): Edward Ma Originally published on Towards AI. Discussing XLMs and unsupervised cross-lingual word embedding by multilingual neural language models Photo by Edward Ma on Unsplash A pre-trained model is proven to improve the downstream problem. Lample and Conneau propose two new …
Attention Is All You Need β Transformer
Author(s): Sherwin Chen Originally published on Towards AI. Positional Encoding Top highlight from https://wall.alphacoders.com/big.php?i=845641 Recurrent Neural Networks(RNNs), Long Short-Term Memory(LSTM) and Gated Recurrent Units(GRU) in particular, have been firmly established as state-of-the-art approaches in sequence modeling and transduction problems. Such models typically …
Getting the data
Author(s): Avishek Nag Originally published on Towards AI. Comparative study of different vector space models & text classification techniques like XGBoost and others In this article, we will discuss different text classification techniques to solve the BBC new article categorization problem. We …
Introduction to the Architecture of Recurrent Neural Networks (RNNs)
Author(s): Manish Nayak Originally published on Towards AI. RNNs Architecture U+007C Towards AI Introduction In my previous post, I explain different ways of representing text as a vector. you can read about Word2Vec, Doc2Vec and you can also find a jupyter notebook …
References
Author(s): Joseph Reddy Originally published on Towards AI. Machine Learning, Python End to End Model of Data Analysis & Prediction Using Python on SAP HANA Table Data This blog helps to connect with SAP HANA DB (Version 1.0 SPS12) then extracts the …
Comparing Neural Network Architectures
Author(s): Yan Gobeil Originally published on Towards AI. Comparing NN architectures through a language classifier, using Google Colab After reading FranΓ§ois Cholletβs wonderful book Deep Learning with Python I became curious about the different neural network architectures and which one is the …
Introduction
Author(s): Manish Nayak Originally published on Towards AI. Machine Learning An Intuitive Introduction of Word2Vec by Building a Word2Vec From Scratch Understanding Word2Vec, and itβs advantages In this article, I will try to explain Word2Vec vector representation, an unsupervised model that learns …
The Basics of Recurrent Neural Networks (RNNs)
Author(s): Ben Khuong Originally published on Towards AI. Top highlight Machine Learning Table of contents What are RNNs used for? What are RNNs and how do they work? A trivial example β forward propagation, backpropagation through time One major problem: vanishing gradients …
Nothing but NumPy: Understanding & Creating Neural Networks with Computational Graphs from Scratch
Author(s): Rafay Khan Originally published on Towards AI. Top highlight Machine Learning, Programming, Python Update: I am overwhelmed by the positive feedback this writeup has received, especially by people in the AI community I look up to. I am also grateful to …
Automate Testing of TensorFlow Lite Model Implementation
Author(s): Mirek Stanek Originally published on Towards AI. Making sure that your ML model works correctly on a mobile app (part 2) This post was originally published at thinkmobile.dev β a blog about implementing intelligent solutions in mobile apps (link to article). …
Computer Vision with fast.ai
Author(s): Dhairya Kumar Originally published on Towards AI. Building and Deploying an Image Classifier U+007C Towards AI Build and deploy an image classifier using fast.ai and Render Computer vision is ubiquitous and it has tons of real-life applications like object detection, face …
Artificial Intelligence
Author(s): Dhairya Kumar Originally published on Towards AI. Intro to Machine Learning, No Math Involved U+007C Towards AI Demystifying Machine Learning A gentle introduction to the scientific field of machine learning with no math involved Machine learning is one of the most …
Beginners Guide to Convolutional Neural Network from Scratch β Kuzushiji-MNIST
Author(s): Satsawat Natakarnkitkul Originally published on Towards AI. Machine Learning Figure 1: Convolutional Neural Network (Source: https://en.wikipedia.org/wiki/Convolutional_neural_network) In the previous post, which you can check it out here, I have demonstrated various dimensional reduction techniques on Kuzushiji-MNIST (KMNIST) data set. In this …