Monday, March 8, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Neural Networks

My Week in AI: Part 4. Welcome to My Week in AI! Each week… | by Anirudh Shah | Jun, 2020

July 15, 2020
in Neural Networks
My Week in AI: Part 4. Welcome to My Week in AI! Each week… | by Anirudh Shah | Jun, 2020
586
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter

Welcome to My Week in AI! Each week this blog will have the following parts:

  • What I have done this week in AI
  • An overview of an exciting and emerging piece of AI research

Discovering Metric Learning

I have spent a lot of time this week reading the latest literature on time series forecasting and visual search, as I am working on projects in these two areas.

You might also like

Deploy AI models -Part 3 using Flask and Json | by RAVI SHEKHAR TIWARI | Feb, 2021

Labeling Service Case Study — Video Annotation — License Plate Recognition | by ByteBridge | Feb, 2021

5 Tech Trends Redefining the Home Buying Experience in 2021 | by Iflexion | Mar, 2021

During my research into visual search, I came across the Pytorch Metric Learning library. Metric learning is automatically building task-specific distance metrics from supervised data instead of using a standard distance metric such as Euclidean distance. This task is especially important for developing a metric to determine image similarity, which is the primary application I was considering. The library allows easy implementation of loss functions and miners with regards to metric learning, such as triplet loss, angular loss, tuple miners and subset batch miners. I believe this is a very convenient library for anyone implementing visual search algorithms.

1. Natural Language Generation:
The Commercial State of the Art in 2020

2. This Entire Article Was Written by Open AI’s GPT2

3. Learning To Classify Images Without Labels

4. Becoming a Data Scientist, Data Analyst, Financial Analyst and Research Analyst

Multivariate Time Series Forecasting

The research I will be featuring this week is on time series forecasting. I have been working on time series forecasting for a year now through my work at Blueprint Power, so I try to keep abreast of the latest advancements in this field.

The forecasting of multivariate time series is challenging as it is high dimensional, has spatial-temporal dependency characteristics and each variable depends not only on its own past values but on the values of other variables, too. Du et al. proposed a novel method of forecasting such time series in their paper, ‘Multivariate time series forecasting via attention-based encoder-decoder framework.’¹

Graphical representation of framework architecture¹

The researchers’ proposed framework was made up of a Bi-LSTM encoder, a temporal attention context layer and an LSTM decoder. The attention layer is important because in a typical encoder-decoder structure, the encoder compresses the hidden representation of the time series into a fixed length vector, which means information can be lost. The temporal attention context vectors are created based on a weighted sum of the hidden states of the encoder, and give context on which parts of these hidden states are most useful to the decoder. This allows the decoder to extract the most useful information from the outputs of the encoder.

In experiments on commonly used time series datasets, this proposed framework performed better than vanilla deep learning models such as LSTM and GRU, and also better than other encoder-decoder architectures. For me, the key takeaways from this research are the use of the Bi-LSTM encoder, which the researchers demonstrated had improved performance over an LSTM encoder, and also that the addition of the attention layer improved performance. These are two methods that I will be looking to integrate into my time series forecasting work in the future.

ML Jobs

Credit: BecomingHuman By: Anirudh Shah

Previous Post

B2B Brand Storytelling: How to Use Empathy

Next Post

Outliers -- Visual Studio Magazine

Related Posts

Deploy AI models -Part 3 using Flask and Json | by RAVI SHEKHAR TIWARI | Feb, 2021
Neural Networks

Deploy AI models -Part 3 using Flask and Json | by RAVI SHEKHAR TIWARI | Feb, 2021

March 6, 2021
Labeling Service Case Study — Video Annotation — License Plate Recognition | by ByteBridge | Feb, 2021
Neural Networks

Labeling Service Case Study — Video Annotation — License Plate Recognition | by ByteBridge | Feb, 2021

March 6, 2021
5 Tech Trends Redefining the Home Buying Experience in 2021 | by Iflexion | Mar, 2021
Neural Networks

5 Tech Trends Redefining the Home Buying Experience in 2021 | by Iflexion | Mar, 2021

March 6, 2021
Labeling Case Study — Agriculture— Pigs’ Productivity, Behavior, and Welfare Image Labeling | by ByteBridge | Feb, 2021
Neural Networks

Labeling Case Study — Agriculture— Pigs’ Productivity, Behavior, and Welfare Image Labeling | by ByteBridge | Feb, 2021

March 5, 2021
8 concepts you must know in the field of Artificial Intelligence | by Diana Diaz Castro | Feb, 2021
Neural Networks

8 concepts you must know in the field of Artificial Intelligence | by Diana Diaz Castro | Feb, 2021

March 5, 2021
Next Post
Outliers — Visual Studio Magazine

Outliers -- Visual Studio Magazine

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

Top 6 Regression Techniques a Data Science Specialist Needs to Know
Data Science

Top 6 Regression Techniques a Data Science Specialist Needs to Know

March 8, 2021
Dataiku named as Gartner Leader for Data Science and Machine Learning
Machine Learning

Dataiku named as Gartner Leader for Data Science and Machine Learning

March 8, 2021
Bill establishing cyber abuse takedown scheme for adults enters Parliament
Internet Security

eSafety defends detail of Online Safety Bill as the ‘sausage that’s being made’

March 8, 2021
An Easy Way to Solve Complex Optimization Problems in Machine Learning
Data Science

An Easy Way to Solve Complex Optimization Problems in Machine Learning

March 8, 2021
Machine Learning Patentability In 2019: 5 Cases Analyzed And Lessons Learned Part 4 – Intellectual Property
Machine Learning

Podcast: Non-Binding Guidance: FDA Regulatory Developments In AI And Machine Learning – Food, Drugs, Healthcare, Life Sciences

March 8, 2021
Here’s an adorable factory game about machine learning and cats
Machine Learning

Here’s an adorable factory game about machine learning and cats

March 8, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • Top 6 Regression Techniques a Data Science Specialist Needs to Know March 8, 2021
  • Dataiku named as Gartner Leader for Data Science and Machine Learning March 8, 2021
  • eSafety defends detail of Online Safety Bill as the ‘sausage that’s being made’ March 8, 2021
  • An Easy Way to Solve Complex Optimization Problems in Machine Learning March 8, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates