Instructional Video7:05
Curated Video

Data Science and Machine Learning with R - Logical Operators

Higher Ed
This video explains logical operators, This clip is from the chapter "Intermediate R" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for 2021]".This section explains intermediate R.
Instructional Video15:05
Flipping Physics

Cross Product Torque (with a Cross Product Review)

12th - Higher Ed
Torque as the cross product is introduced. How to actually perform the cross product using matrices is reviewed and 4.5 examples are walked through. This is an AP Physics C: Mechanics topic. Content Times: 0:00 Torque Review 0:55 Cross...
Instructional Video6:40
FuseSchool

MATHS - Trigonometry - Vectors

6th - Higher Ed
Physical properties like area, volume and temperature - are scalars, since we only need a number to represent them. But when we deal with other properties, such as velocity and acceleration, we may use both a ‘size’ and a direction. Such...
Instructional Video8:35
Flipping Physics

Conservation of Momentum Derivation and Rocket Demonstration

12th - Higher Ed
Newton’s Second Law in terms of Momentum is introduced and used to derive Conservation of Linear Momentum. A water rocket in slow motion is used to demonstrate this as well. Want Lecture Notes?...
Instructional Video6:45
Brian McLogan

Master how to find if two vectors are orthagonal, parallel or neither

12th - Higher Ed
Master how to find if two vectors are orthagonal, parallel or neither
Instructional Video14:46
Schooling Online

Physics Kinematics: Motion in a Straight Line - Algebraic Vector Addition and Subtraction

3rd - Higher Ed
Vector Man and the police have no clue about how to interpret Lexi Luthor’s blueprints… This looks like a job for Lotus! This lesson will explain the steps needed to algebraically add and subtract 2D vectors. Definitions included:...
Instructional Video11:55
Virtually Passed

Relative velocity (with rotating axes) Proof

Higher Ed
If the relative axes xy aren't rotating (w = 0) then the velocity equation becomes Va = Vb + Va/b However, in general, relative reference axes can rotate and the following relative velocity equation becomes Va = Vb + Vrel + Vp/b Note...
Instructional Video13:20
Curated Video

Rust Programming Master Class from Beginner to Expert - Compound Data Types - Vectors

Higher Ed
In this video, we will cover compound data types such as vectors. This clip is from the chapter "Basic Programming" of the series "Rust Programming Master Class from Beginner to Expert".In this section, you will learn the fundamentals of...
Instructional Video8:58
Curated Video

Reinforcement Learning and Deep RL Python Theory and Projects - DNN Implementation Minibatch Gradient Descent

Higher Ed
This video explains about the implementation of minibatch gradient descent. This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses...
Instructional Video6:14
Curated Video

Fundamentals of Machine Learning - PCA

Higher Ed
This video explains a lab session on Eigenfaces using PCA. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on linear regression, ridge regression,...
Instructional Video7:49
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Feature Engineering: Derived Features Histogram of Gradients Local Binary Patterns

Higher Ed
In this video, we will cover derived features histogram of gradients local binary patterns. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and...
Instructional Video4:21
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Regression Exercise Solution

Higher Ed
In this video, we will cover regression exercise solution. 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...
Instructional Video11:21
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Classification Solution

Higher Ed
In this video, we will cover classification solution. 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,...
Instructional Video8:36
Curated Video

Vectors: Theory

9th - 12th
This video shows the use of vector theory to work out the coordinates of points on a parallelogram. It also shows how to use a vector method to prove that points on a parallelogram form a straight line. Source of question: IGCSE A June...
Instructional Video19:55
Curated Video

Practical Data Science using Python - Principal Component Analysis - Computations 1

Higher Ed
This video explains Principal Component Analysis – computations. This clip is from the chapter "Dimensionality Reduction Using PCA" of the series "Practical Data Science Using Python".This section explains dimensionality reduction using...
Instructional Video11:28
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Feature Extraction: PCA Versus SVD

Higher Ed
In this video, we will cover PCA versus SVD. 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 Projects) A to Z".In...
Instructional Video10:38
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Feature Extraction: PCA For Small Sample Size Problems(DualPCA)

Higher Ed
In this video, we will cover PCA for small sample size problems (DualPCA). This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning...
Instructional Video9:04
Curated Video

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

Higher Ed
In this video, we will cover DNN implementation minibatch gradient descent. 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...
Instructional Video3:21
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: ManyToMany Model Solution 02

Higher Ed
In this video, we will cover ManyToMany model solution 02. 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 Video2:05
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: ManyToMany Model Exercise 01

Higher Ed
In this video, we will cover ManyToMany model exercise 01. 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 Video14:59
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Project I_ Book Writer: Data Mapping

Higher Ed
In this video, we will cover data mapping. 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 Video5:18
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Sentiment Classification using RNN: Vectorizer

Higher Ed
In this video, we will cover Vectorizer. 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 Video25:56
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - TensorFlow: TensorFlow Text Classification Example using RNN

Higher Ed
In this video, we will cover TensorFlow text classification example using RNN. 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...
Instructional Video7:16
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Rank

Higher Ed
In this video, we will cover Rank. 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 Projects) A to Z".In this...