Instructional Video3:22
Curated Video

Deep Learning - Deep Neural Network for Beginners Using Python - Use of Derivatives

Higher Ed
In this video, we will discuss the uses of derivatives. This clip is from the chapter "Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will dive deeper into deep learning.
Instructional Video2:29
Curated Video

Deep Learning - Deep Neural Network for Beginners Using Python - Sigma Prime

Higher Ed
In this video, you will learn about Sigma Prime. This clip is from the chapter "Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will dive deeper into deep learning.
Instructional Video2:39
Curated Video

Deep Learning - Deep Neural Network for Beginners Using Python - Convex Functions

Higher Ed
In this video, we will discuss about convex functions. This clip is from the chapter "Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will dive deeper into deep learning.
Instructional Video9:05
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Applying Chain Rule

Higher Ed
In this video, we will cover applying chain rule. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we...
Instructional Video11:08
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: Backpropagation

Higher Ed
In this video, we will cover backpropagation. This clip is from the chapter "Deep learning: Artificial Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
Instructional Video9:25
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Image Processing: Edge Detection

Higher Ed
In this video, we will cover edge detection. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
Instructional Video2:50
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in RNN: Why Gradients Solution

Higher Ed
In this video, we will understand why gradients solution. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this...
Instructional Video6:07
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in RNN: Why Gradients

Higher Ed
In this video, we will understand why gradients. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
Instructional Video8:06
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in RNN: Loss Function

Higher Ed
In this video, we will cover loss function. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
Instructional Video10:29
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Why Derivatives

Higher Ed
In this video, we will understand why derivatives. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section,...
Instructional Video8:20
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Gradients of Convolutional Layer

Higher Ed
In this video, we will cover gradients of convolutional layer. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In...
Instructional Video9:01
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Extending to Multiple Filters

Higher Ed
In this video, we will cover extending to multiple filters. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this...
Instructional Video3:31
Brian McLogan

Learn how to find the derivative of tangent using the quotient rule

12th - Higher Ed
👉 Learn how to find the derivative of a function using the quotient rule. The derivative of a function, y = f(x), is the measure of the rate of change of the function, y, with respect to the variable x. The process of finding the...
Instructional Video9:31
Brian McLogan

Solving a falling ladder problem using related rates

12th - Higher Ed
👉 Learn how to take the derivative of a function. Learn how to find the derivative of a function using the chain rule. The derivative of a function, y = f(x), is the measure of the rate of change of the function, y, with respect to the...
Instructional Video10:04
Math Fortress

Calculus I: Derivatives of Polynomials and Natural Exponential Functions (Level 1 of 3)

12th - Higher Ed
This video will teach you the basics of calculating the derivative of simple polynomials and exponential functions.
Instructional Video2:46
Tarver Academy

One Piece of Advice for Starting School

12th - Higher Ed
In This Episode, Tyler Teaches Us About One Piece of Advice for Starting School
Instructional Video4:30
Brian McLogan

Find the derivative using product rule inside quotient

12th - Higher Ed
👉 Learn how to find the derivative of a function using the quotient rule. The derivative of a function, y = f(x), is the measure of the rate of change of the function, y, with respect to the variable x. The process of finding the...
Instructional Video6:50
msvgo

Structure of DNA

K - 12th
This nugget describes historical aspect of discovery of nucleic acid, basic structure of polynucleotide chain, Watson model of DNA and types of DNA.
Instructional Video4:11
Brian McLogan

If a function is differentiable then it is continuous

12th - Higher Ed
👉 Learn how to determine the differentiability of a function. A function is said to be differentiable if the derivative exists at each point in its domain. To check the differentiability of a function, we first check that the function is...
Instructional Video10:12
Professor Dave Explains

Evaluating Indefinite Integrals

12th - Higher Ed
How to evaluate indefinite integrals.
Instructional Video11:21
Professor Dave Explains

Derivatives of Polynomial Functions: Power Rule, Product Rule, and Quotient Rule

12th - Higher Ed
The derivation of the product rule and quotient rule for taking derivatives in calculus.
Instructional Video10:17
Math Fortress

Differential Equations: Definitions and Terminology (Level 4 of 4)

12th - Higher Ed
This video introduces the basic definitions and terminology of differential equations. This video goes over 8 examples covering how to classify Partial Differential Equations (PDE) by order and linearity.
Instructional Video4:45
msvgo

Derivatives of Functions in Parametric Forms

K - 12th
It explains how to find the derivatives of functions which are in parametric form.
Instructional Video2:32
Brian McLogan

Learn the basics to implicit differentiation

12th - Higher Ed
👉 Learn how to find the derivative of an implicit function. The derivative of a function, y = f(x), is the measure of the rate of change of the function, y, with respect to the variable x. The process of finding the derivative of a...