Instructional Video9:03
Professor Dave Explains

Change of Basis

9th - Higher Ed
How to perform a change of basis on a system of equations.
Instructional Video8:12
Professor Dave Explains

Diagonalization

12th - Higher Ed
Performing diagonalization.
Instructional Video5:14
IDG TECHtalk

NumPy, the Python library for faster math and data science apps

Higher Ed
The NumPy library accelerates Python's number-crunching powers, while keeping Python's ease of use and flexibility. Learn in this video the basics of NumPy's use, where it shines, and where it's less effective.
Instructional Video2:00
Instructional Video21:20
Why U

Algebra 54 - Gaussian Elimination

12th - Higher Ed
A system of linear equations represented as an augmented matrix can be simplified through the process of Gaussian elimination to row echelon form. At that point the matrix can be converted back into equations which are simpler and easy...
Instructional Video12:14
Curated Video

The Complete Java Developer Course: From Beginner to Master - 2D Arrays (Side Topic)

Higher Ed
This video explains about the 2D arrays. This clip is from the chapter "Methods" of the series "The Complete Java Developer Course: From Beginner to Master".This section explains Methods that are a set of blocks of code that resolves a...
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 Video4:02
Curated Video

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

Higher Ed
In this video, we will cover DNN implementation gradient step. 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 Video11:31
Curated Video

AWS Cloud Development Kit - From Beginner to Professional - CloudWatch Live Dashboards and Widgets

Higher Ed
This video explains CloudWatch live dashboards and widgets. This clip is from the chapter "Create and Deploy Serverless Application Resources" of the series "AWS Cloud Development Kit - From Beginner to Professional".In this section, you...
Instructional Video7:56
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - NumPy for Numerical Data Processing: Slicing-Part 2

Higher Ed
In this video, we will cover slicing-part 2. This clip is from the chapter "Basics for Data Science: Python for Data Science and Data Analysis" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this...
Instructional Video9:08
Curated Video

Deep Learning CNN Convolutional Neural Networks with Python - Implementation in NumPy BackwardPass 3

Higher Ed
This is third of the five-part video on implementation in NumPy BackwardPass. This clip is from the chapter "Gradient Descent in CNNs" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on...
Instructional Video4:42
Curated Video

Reinforcement Learning and Deep RL Python Theory and Projects - DNN Why Activation Function Is Required

Higher Ed
This video explains why activation function is required in DNN. 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 on the DNN...
Instructional Video3:57
Curated Video

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

Higher Ed
This video explains about the implementation of the gradient step. 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 on the DNN...
Instructional Video4:48
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN Why Activation Function Is Required

Higher Ed
In this video, we will understand why activation function is required. 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 Video7:27
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - RNN Implementation: Language Modelling Next Word Prediction Python 3

Higher Ed
In this video, we will cover language modelling next word prediction Python 3. 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 Video6:35
Instructional Video7:48
Curated Video

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

Higher Ed
In this video, we will cover RGB images. 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 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 Video1:45
Curated Video

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

Higher Ed
In this video, we will cover equations exercise. 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 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 Video3:50
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Seaborn for Data Visualization: Seaborn Heatmaps

Higher Ed
In this video, we will cover Seaborn Heatmaps. This clip is from the chapter "Basics for Data Science: Data Understanding and Data Visualization with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to...
Instructional Video8:37
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Positive Semi Definite Matrix

Higher Ed
In this video, we will cover a positive semi definite matrix. 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 Video11:02
Curated Video

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

Higher Ed
In this video, we will cover Lagrange Multipliers. 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...
Instructional Video3:55
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Introduction to Mathematical Foundation of Feature Selection

Higher Ed
In this video, we will cover an introduction to mathematical foundation of feature selection. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and...