Instructional Video6:00
Curated Video

Deep Learning - Deep Neural Network for Beginners Using Python - Chain Rule for Backpropagation

Higher Ed
In this video, you will learn about the chain rule for backpropagation. 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...
Instructional Video6:43
Curated Video

Deep Learning - Deep Neural Network for Beginners Using Python - Basics of Backpropagation

Higher Ed
In this video, you will learn about basics of backpropagation. 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...
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 Video6:52
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN Gradient Descent Implementation

Higher Ed
In this video, we will cover DNN gradient descent implementation. 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...
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 Video9:04
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Object Detection: HOG Features

Higher Ed
In this video, we will cover HOG features. 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 Video5:58
Curated Video

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

Higher Ed
In this video, we will cover chain rules in action. 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...
Instructional Video7:29
Curated Video

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

Higher Ed
In this video, we will cover chain rules. 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 cover...
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 Video12:21
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Implementation in NumPy BackwardPass 4

Higher Ed
In this video, we will cover implementation in NumPy BackwardPass 4. 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...
Instructional Video9:08
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Implementation in NumPy BackwardPass 3

Higher Ed
In this video, we will cover implementation in NumPy BackwardPass 3. 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...
Instructional Video4:37
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Implementation in NumPy BackwardPass 2

Higher Ed
In this video, we will cover implementation in NumPy BackwardPass 2. 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...
Instructional Video6:48
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Implementation in NumPy BackwardPass 1

Higher Ed
In this video, we will cover implementation in NumPy BackwardPass 1. 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...
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 Video6:21
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Linear Algebra Module Python

Higher Ed
In this video, we will cover linear algebra module Python. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and...
Instructional Video1:51
Brian McLogan

Determine the derivative expanding a binomial to use the power rule

12th - Higher Ed
👉 Learn how to find the derivative of a function using the power 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 derivative...
Instructional Video8:38
Institute for New Economic Thinking

Janine Wedel - Behind the Scenes of International Banking Regulation

Higher Ed
Five years into the Great Recession, discussion and political fights continue about the right approach to international banking supervision. How to avert the next financial crisis or at the very least lessen its damage? Given the topic's...
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 Video2:07
Brian McLogan

Implicit differentiation using the product rule

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...
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.