Learn How to Get Discord Threads

Learn how to get Discord Threads: a new Discord feature like profile customization! In this video, I show you how to enable Discord Threads for your Discord Server, and then create a thread in your server! This does not seem to be an experiment or beta feature like the Discord Profile Banner and About Me features were.


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Learn How to Get Discord Threads

Frank Xu


Thread Gauge Calibration - What Should You Know?

If you are using thread gauges or thread ring gauges you would have already heard about calibration. If you do not pay attention to thread gauge calibration then the integrity of the thread gauges you are purchasing and using could be compromised. In case you do not know what is thread gauge calibration and what is its significance then here are a few important factors that you should know about calibration.

When you order a custom trapezoidal thread gauge or a custom Whitworth thread gauge or for that matter any thread gauge, how will you know that it is exactly matching your requirements and specifications? As you know the thread gauges are inspection tools and unless they are 100% accurate there is no use having a thread gauge. When you calibrate the thread gauge you will know whether or not the tool is true to its specifications and whether it matches the required specifications 100%.

It is important to get calibration certificate along with your thread gauge when ever you are purchasing your thread gauge. All the manufacturers will arrange for a third party calibration certificate if you inform them early enough while placing your order. This may have an additional cost but you cannot avoid this cost because without having the confirmation that your thread gauge is delivered as per your requirements, you cannot confidently check the components that need to be inspected with your thread gauges. If there is any issue with the thread gauge you will think that there is something wrong with the threaded components. As a result, you would keep rejecting those components when the actual issue is with the thread gauge you are using. All such issues and mistakes could be avoided or minimized when you go for a calibration certificate when you are buying your thread gauges.

You may need to go for recalibration every time you repair your thread gauge or make any modifications to it. In case you are experiencing sudden episode of issues with your threaded components then it is best to first check the thread gauges you are using to ensure that the problem is not with the thread gauge.

It is also important to get a calibration certificate for your thread gauge if the tool has been dropped or if someone that is not trained properly use the thread gauge and exerts undue force. In other words, whenever you suspect that the thread gauge could have been damaged then it is vital go check the thread gauge and calibrate it so that you can be sure of the accuracy of the thread gauge.

Always source all your thread gauges from the most trusted companies. Whenever you are calibrating your thread gauge get it done from a reputed calibration center. You cannot afford to have a faulty thread gauge as it is an inspection tool, a standard that is used to measure the accuracy of the other tools. Therefore, make sure that your thread gauges are always well maintained and regularly calibrated.

#trapezoidal thread gauge #thread gauges #thread ring gauges #thread plug gauges #metric thread gauges #unef thread gages

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 — 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

Obie  Rowe

Obie Rowe


How To Get Started With Machine Learning With The Right Mindset

You got intrigued by the machine learning world and wanted to get started as soon as possible, read all the articles, watched all the videos, but still isn’t sure about where to start, welcome to the club.

Before we dive into the machine learning world, you should take a step back and think, what is stopping you from getting started? If you think about it, most of the time, we presuppose things about ourselves and assume that to be true without question.

The most normal presumption that we make about ourselves is that we need to have prior knowledge before getting started. Get a degree, complete a course, or have a good understanding of a particular subject.

The truth is that most of the time, this is a lie, the prior knowledge you think you need is most of the time not required or is so big that even experts from the field don’t fully understand it. The Seek of this prior knowledge is a trap that will make you run in circles, which leads us to the next presumption.

The perfect condition, you can’t wait for the ideal environment or situation to get started, things will never be 100% ready, try and fail, then try again. It takes a lot of time to get good at machine learning; you won’t learn all at once and especially at the beginning.

Instead of trying to acknowledge everything before getting started, do a little bit every day; you can make significant progress by creating small things every day for a considerable amount of time. The perfect condition will never exist, do it in your path, be consistent with it, and the results will come.

After you start making little progress every day, you probably will end up having a struggle with something or failing to achieve your goal at a certain point. This feeling is tough; it’s hard to see yourself not making any progress, not having any sense of gratification, and then still not give up.

Machine learning is hard, it might take you a few weeks, months or even years to see progress in a certain point but isn’t any harder than any other technical skill, it requires repetition and dedication to get where you want, you need to test it, make a mistake and learn from i

#machine-learning #artificial-intelligence #python-machine-learning #learn-machine-learning #latest-tech-stories #machine-learning-uses #ml-top-story #ai-and-ml

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

Why you should learn Computer Vision and how you can get started

I. Motivation

In today’s world, Computer Vision technologies are everywhere. They are embedded within many of the tools and applications that we use on a daily basis. However, we often pay little attention to those underlaying Computer Vision technologies because they tend to run in the background. As a result, only a small fraction of those outside the tech industries know about the importance of those technologies. Therefore, the goal of this article is to provide an overview of Computer Vision to those with little to no knowledge about the field. I attempt to achieve this goal by answering three questions: What is Computer Vision?, Why should you learn Computer Vision? and How you can get started?

II. What is Computer Vision?

Image for post

Figure 1: Portrait of Larry Roberts.
The field of Computer Vision dates back to the 1960s when Larry Roberts, who is now widely considered as the “Father of Computer Vision”, published his paper _Machine Perception of Three-Dimensional Solids _detailing how a computer can infer 3D shapes from a 2D image (Roberts, 1995). Since then, other researchers have made amazing contributions to the field. These advances, however, have not changed the underlaying goal of Computer Vision which is to mimic the human visual system. From an engineering point of view, this means being able to build autonomous systems that can do things a human visual system can do such as detecting and recognizing objects, recognizing faces and facial expressions, etc. (Huang, 1996). Traditionally, many approaches in Computer Vision involves manual feature extraction. This means manually finding some unique features/characteristics (edges, shapes, etc) that are only present in an object to be able to detect and recognize what that object is. Unfortunately, one major issue arises when trying to detect and recognize variations (sizes, lightning conditions, etc) of that same object. It is difficult to find features that can uniquely identify an object across all variations. Fortunately, this problem is now solved with the introduction of Machine Learning, particularly a sub-field of Machine Learning called Deep Learning. Deep Learning utilizes a form of Neural Networks called Convolutional Neural Networks (CNNs). Unlike the traditional methods, methods that utilize CNNs are able to extract features automatically. Instead of trying to figure out which features can represent an object manually, a CNN can learn those features automatically by looking at many variations of that same object. As result, many recent advancements in the field of Computer Vision involves the use of CNNs.

#computer-science #machine-learning #deep-learning #computer-vision #learning #deep learning