## What is the Difference Between a Batch and an Epoch in a Neural Network?

Stochastic gradient descent is a learning algorithm that has a number of hyperparameters. Two hyperparameters that often confuse beginners are the batch size and number of epochs. They are both integer values and seem to do the same thing. In this post, you will discover…

## Is your name also a NUMBER? | Find what number your name is with math and code

In base-36, the number 360927794919225 is expressed using the numeral deeplizard. Yes. Everyone’s name is also a number in some base. Let’s check this out. Notebook links: https://beta.observablehq.com/@deeplizard/positional-numeral-systems https://beta.observablehq.com/@deeplizard/find-the-numbers-for-your-name Follow deeplizard: YouTube: https://www.youtube.com/deeplizard Twitter: https://twitter.com/deeplizard Facebook: https://www.facebook.com/Deeplizard-145413762948316 Steemit: https://steemit.com/@deeplizard Instagram: https://www.instagram.com/deeplizard/ Pinterest: https://www.pinterest.com/deeplizard/ Support deeplizard…

## 5 Patterns with Numbers – Binary to Base-36 | Numerals across bases

What numeral is used to express the number 17 in base-16. a) 17 b) 1 c) 11 d) 2 Soon you’ll be able to snap answer questions like this one for any base. This is due to one of the patterns I’m about show you…

## Hexadecimal explained | Higher than base-10 positional numeral systems

A digit is a single symbol that represents a number. In positional numeral systems, the base tells us how many distinct digits we have to express numbers using numerals. Base-2 has two digits. Base-3 has 3 digits, and this pattern holds all the way up…

## Numeral vs Number | Introducing numeral systems for programming beginners

What’s the difference between the number 12 and the numeral 12? A numeral system is any writing system that allows us to express numbers using symbols. When we express a number using symbols, the result is called a numeral. When we express a number using…

## Is it Possible that AI Can Solve the Problems Einstein Couldn’t? – AI Trends

At the dawn of the 20th century, there were a number of crises in physics. Radiating objects like stars emitted a finite, well-defined amount of energy at every wavelength, defying the best predictions of the day. Newton’s laws of motion broke down and failed when objects approached…

## Learnable parameters (“trainable params”) in a Keras Convolutional Neural Network

In this video, we’ll discuss how we can quickly access and calculate the number of learnable parameters in a convolutional neural network (CNN) in code with Keras. We’ll also explore how these parameters may be affected by other optional configurations, like max pooling and zero…

## Learnable parameters (“trainable params”) in a Keras model

In this video, we’ll discuss how we can quickly access and calculate the number of learnable parameters in a Keras Sequential model. We do this by inspecting and verifying the results in the “Param #” column of model.summary(). We then inspect the parameters returned from…

## Why are healthcare providers scared of exercise? | PLOS Blogs Network

Over the past few years I’ve had the pleasure of meeting with a number healthcare providers to discuss the role and importance of exercise for their patients.  In those interactions, I’ve noted 2 common themes VISIT THE SOURCE ARTICLE Why are healthcare providers scared of…

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## Backpropagation explained | Part 4 – Calculating the gradient

We’re now on video number 4 in our journey through understanding backpropagation. In our last video, we focused on how we can mathematically express certain facts about the training process. Now we’re going to be using these expressions to help us differentiate the loss of…