Tanner  Smith

Tanner Smith


Learn to Closures - Rust

π—œπ— π—£π—’π—₯𝗧𝗔𝗑𝗧: At 8:17, I finish the example for π™΅πš— but… I missed an ampersand πŸ€¦β€β™‚οΈ ~ consequently, that example does not demonstrate an immutable borrow because x implements the Copy trait. A better example would be:

πš•πšŽπš 𝚑𝟷 = 𝟷;
πš•πšŽπš πš˜πš”πŸ· = | | &𝚑𝟷 + 𝟷;
πš™πš›πš’πš—πšπš•πš—!(β€œ{:?}” , πš˜πš”πŸ·( ));
πš™πš›πš’πš—πšπš•πš—!(β€œ{:?}” , 𝚑𝟷);

Thanks @Nicholas Sterling for catching this mistake πŸ”₯

Chapter 13.1

#rust #closures

Learn to Closures - Rust
Jerad  Bailey

Jerad Bailey


Google Reveals "What is being Transferred” in Transfer Learning

Recently, researchers from Google proposed the solution of a very fundamental question in the machine learning community β€” What is being transferred in Transfer Learning? They explained various tools and analyses to address the fundamental question.

The ability to transfer the domain knowledge of one machine in which it is trained on to another where the data is usually scarce is one of the desired capabilities for machines. Researchers around the globe have been using transfer learning in various deep learning applications, including object detection, image classification, medical imaging tasks, among others.

#developers corner #learn transfer learning #machine learning #transfer learning #transfer learning methods #transfer learning resources

Google Reveals "What is being Transferred” in Transfer Learning
sophia tondon

sophia tondon


5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

#machinelearningapps #machinelearningdevelopers #machinelearningexpert #machinelearningexperts #expertmachinelearningservices #topmachinelearningcompanies #machinelearningdevelopmentcompany

Visit Blog- https://www.xplace.com/article/8743

#machine learning companies #top machine learning companies #machine learning development company #expert machine learning services #machine learning experts #machine learning expert

5 Latest Technology Trends of Machine Learning for 2021
Lydia  Kessler

Lydia Kessler


ULTIMATE Rust Lang Tutorial! - Closures in Rust

The ultimate Rust lang tutorial. Follow along as we go through the Rust lang book chapter by chapter.

πŸ“Get the FREE Rust Cheatsheet: https://letsgetrusty.com/cheatsheet

The Rust book: https://doc.rust-lang.org/stable/book/​​

0:00​ Intro
0:29 What Are Closures?
0:50 Example Program
2:55 Refactoring With Functions
4:07 Refactoring Using Closures
6:31 Type Inference And Annotation
8:06 Generic Parameters And Fn Traits
15:33 Capturing the Environment with Closures
19:12 Outro

#letsgetrusty​​ #rust​lang​ #tutorial

#rust #rust lang #closures

ULTIMATE Rust Lang Tutorial! - Closures in Rust
Jackson  Crist

Jackson Crist


Intro to Reinforcement Learning: Temporal Difference Learning, SARSA Vs. Q-learning

Reinforcement learning (RL) is surely a rising field, with the huge influence from the performance of AlphaZero (the best chess engine as of now). RL is a subfield of machine learning that teaches agents to perform in an environment to maximize rewards overtime.

Among RL’s model-free methods is temporal difference (TD) learning, with SARSA and Q-learning (QL) being two of the most used algorithms. I chose to explore SARSA and QL to highlight a subtle difference between on-policy learning and off-learning, which we will discuss later in the post.

This post assumes you have basic knowledge of the agent, environment, action, and rewards within RL’s scope. A brief introduction can be found here.

The outline of this post include:

  • Temporal difference learning (TD learning)
  • Parameters
  • QL & SARSA
  • Comparison
  • Implementation
  • Conclusion

We will compare these two algorithms via the CartPole game implementation. This post’s code can be found here :QL code ,SARSA code , and the fully functioning code . (the fully-functioning code has both algorithms implemented and trained on cart pole game)

The TD learning will be a bit mathematical, but feel free to skim through and jump directly to QL and SARSA.

#reinforcement-learning #artificial-intelligence #machine-learning #deep-learning #learning

Intro to Reinforcement Learning: Temporal Difference Learning, SARSA Vs. Q-learning

E-learning Software Services - SISGAIN

SISGAIN is one of the top e-Learning software companies in New York, USA. Develop Education Technology based, mobile application for e-learning from SISGAIN. We Develop User Friendly Education App and Provide e-learning web portals development Service. Get Free Quote, Instant Support & End to End Solution. SISGAIN has been developing educational software and provides e-learning application development services for US & UK clients. For more information call us at +18444455767 or email us at [email protected]

#learning development companies #development of software for e-learning #top e-learning software companies #e-learning web portals #mobile applications for e-learning #e-learning product development

E-learning Software Services - SISGAIN