Category: Machine Learning

Articles About Machine Learning

Machine Learning, NLP

BErt-like Neurophysiological Data Representation

BENDR BErt-like Neurophysiological Data Representation. This repository contains the source code for reproducing, or extending the BERT-like self-supervision pre-training for EEG data from the article: BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data To run these scripts, you will need to use the DN3 project. We will try to keep this updated so that it works with the latest DN3 release. If you are just looking for the BENDR model, and […]

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Machine Learning, NLP

Official implementation of Monocular Quasi-Dense 3D Object Tracking

qd-3dt Monocular Quasi-Dense 3D Object Tracking (QD-3DT) is an online framework detects and tracks objects in 3D using quasi-dense object proposals from 2D images. Monocular Quasi-Dense 3D Object Tracking,Hou-Ning Hu, Yung-Hsu Yang, Tobias Fischer, Trevor Darrell, Fisher Yu, Min Sun,arXiv technical report (arXiv 2103.07351)Project Website (QD-3DT) @article{Hu2021QD3DT, author = {Hu, Hou-Ning and Yang, Yung-Hsu and Fischer, Tobias and Yu, Fisher and Darrell, Trevor and Sun, Min}, title = {Monocular Quasi-Dense 3D Object Tracking}, journal = {ArXiv:2103.07351}, year = {2021} } […]

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Machine Learning, NLP

A GitHub bot to automatically update and merge GitHub PRs

kodiak A GitHub bot to automatically update and merge GitHub PRs. install app | documentation | web dashboard Automate your GitHub Pull Requests Auto Update – Keep your PRs up to date with master automatically Auto Merge – Add the automerge label to auto merge once CI and Approvals pass. Bot Collaboration – Combine Kodiak with a dependency bot (dependabot, snyk, greenskeeper.io) to automate updating of dependencies Installation Kodiak is available through the GitHub Marketplace. If you’d rather run Kodiak […]

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Machine Learning

Simple Genetic Algorithm From Scratch in Python

The genetic algorithm is a stochastic global optimization algorithm. It may be one of the most popular and widely known biologically inspired algorithms, along with artificial neural networks. The algorithm is a type of evolutionary algorithm and performs an optimization procedure inspired by the biological theory of evolution by means of natural selection with a binary representation and simple operators based on genetic recombination and genetic mutations. In this tutorial, you will discover the genetic algorithm optimization algorithm. After completing […]

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Machine Learning

How to Update Neural Network Models With More Data

Deep learning neural network models used for predictive modeling may need to be updated. This may be because the data has changed since the model was developed and deployed, or it may be the case that additional labeled data has been made available since the model was developed and it is expected that the additional data will improve the performance of the model. It is important to experiment and evaluate with a range of different approaches when updating neural network […]

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Beginner, Career, Computer Vision, Machine Learning, NLP Leave a comment

Quick Guide to AI and ML Universe for Business Leaders

This article was published as a part of the Data Science Blogathon. Introduction Ever since the advent of Globalisation, the environment in which a business operates is constantly changing. An important component of the business environment is the technological environment. Technology, also, as we all know is constantly changing, updating with new trends coming in every day. Thus, it becomes imperative for businesses to understand and keep up with the technology trends to survive in the market. One thing that […]

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Machine Learning

How to Prepare Movie Review Data for Sentiment Analysis (Text Classification)

Last Updated on December 21, 2020 Text data preparation is different for each problem. Preparation starts with simple steps, like loading data, but quickly gets difficult with cleaning tasks that are very specific to the data you are working with. You need help as to where to begin and what order to work through the steps from raw data to data ready for modeling. In this tutorial, you will discover how to prepare movie review text data for sentiment analysis, […]

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Machine Learning

Differential Evolution Global Optimization With Python

Differential Evolution is a global optimization algorithm. It is a type of evolutionary algorithm and is related to other evolutionary algorithms such as the genetic algorithm. Unlike the genetic algorithm, it was specifically designed to operate upon vectors of real-valued numbers instead of bitstrings. Also unlike the genetic algorithm it uses vector operations like vector subtraction and addition to navigate the search space instead of genetics-inspired transforms. In this tutorial, you will discover the Differential Evolution global optimization algorithm. After […]

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Machine Learning

Evolution Strategies From Scratch in Python

Evolution strategies is a stochastic global optimization algorithm. It is an evolutionary algorithm related to others, such as the genetic algorithm, although it is designed specifically for continuous function optimization. In this tutorial, you will discover how to implement the evolution strategies optimization algorithm. After completing this tutorial, you will know: Evolution Strategies is a stochastic global optimization algorithm inspired by the biological theory of evolution by natural selection. There is a standard terminology for Evolution Strategies and two common […]

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Machine Learning

Prediction Intervals for Deep Learning Neural Networks

Prediction intervals provide a measure of uncertainty for predictions on regression problems. For example, a 95% prediction interval indicates that 95 out of 100 times, the true value will fall between the lower and upper values of the range. This is different from a simple point prediction that might represent the center of the uncertainty interval. There are no standard techniques for calculating a prediction interval for deep learning neural networks on regression predictive modeling problems. Nevertheless, a quick and […]

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