AI News, Will deep learning make other machine learning algorithms obsolete?

Will deep learning make other machine learning algorithms obsolete?

For this reason, there will always be cases where Deep Learning will not be preferred, even if it has managed to squeeze an extra 1% in accuracy on the testing set.

Let's imagine that your very demanding boss asks you to implement an image classifier to detect whether sport images contain scenes coming from a American Football game or a Association Football game.

You are well read in Deep Learning literature, so you train a two-class classifier using Convolutional Neural Networks (CNN) feeding it thousands of labeled images containing both sports.

As a matter of fact, in this example, a dumb classifier that just labels everything as Futbol for this dataset would manage to have much more than a 95% accuracy and would work much better than your fancy Deep Neural Network!

In any case, this simple example proves that you will always have the need to understand your domain and do some feature engineering, favor simple models whenever possible, and most likely use ensembles.

Predicting the Winning Team with Machine Learning

Can we predict the outcome of a football game given a dataset of past games? That's the question that we'll answer in this episode by using the scikit-learn ...

How to Make a Prediction - Intro to Deep Learning #1

Welcome to Intro to Deep Learning! This course is for anyone who wants to become a deep learning engineer. I'll take you from the very basics of deep learning ...

The Best Way to Visualize a Dataset Easily

In this video, we'll visualize a dataset of body metrics collected by giving people a fitness tracking device. We'll go over the steps necessary to preprocess the ...

TRI3D tensorflow.js Distributed Deep Learning

SmartCrop is an experimental feature in beta. We plan to make the training distributed.

What makes high-dimensional networks produce low-dimensional activity?

Eric Shea-Brown, University of Washington Abstract: There is an avalanche of new data on the brain's activity, revealing the collective dynamics of vast numbers ...

Sergey Nikolenko presents a brief survey of deep neural networks for object detection, AI Ukraine 17

Sergey Nikolenko, Chief Research Officer of Neuromation.io, presented his findings on the use of deep neural networks in image recognition during the AI ...

3D Segmentation

In order to track dynamic objects in a robot's environment, one must first segment the scene into a collection of separate objects. Most real-time robotic vision ...

ArtTrack: Articulated Multi-Person Tracking in the Wild

Eldar Insafutdinov, Mykhaylo Andriluka, Leonid Pishchulin, Siyu Tang, Evgeny Levinkov, Bjoern Andres, Bernt Schiele In this paper we propose an approach for ...

Image Recognition and Python Part 1

Sample code for this series: There are many applications for image recognition. One of the largest that ..

Lecture 16: Dynamic Neural Networks for Question Answering

Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"". Key phrases: Coreference Resolution, Dynamic Memory ...