Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Image Processing: RGB Images
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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Image Processing: Grayscale Images
In this video, we will cover grayscale 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in RNN: Why Gradients
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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in RNN: Equations Solution
In this video, we will cover equations 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 section, we will...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Implementation in NumPy ForwardPass.mp4.
In this video, we will cover implementation in NumPy ForwardPass.mp4. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Optional Estimation: Ridge Regression
In this video, we will cover ridge regression.
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Image Processing: Image Formation
In this video, we will cover image formation. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Seaborn for Data Visualization: Seaborn Heatmaps
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...
Curated Video
Business Intelligence with Microsoft Power BI - with Material - Sub-Total and Total in a Matrix
This video explains how to calculate subtotal and total in a matrix. This clip is from the chapter "Tables and Matrix in Power BI" of the series "Business Intelligence with Microsoft Power BI - with Material".This section provides an...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Lagrange Multipliers
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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Vector Derivatives
In this video, we will cover vector derivatives. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Rank
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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Positive Semi Definite Matrix
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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Matrix Product
In this video, we will cover Matrix Product. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Linear Algebra Module Python
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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Introduction to Mathematical Foundation of Feature Selection
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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Eigen Space
In this video, we will cover Eigen Space. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Model Performance Metrics: The Confusion Matrix
In this video, we will cover the confusion matrix. This clip is from the chapter "Machine Learning: Machine Learning Crash Course" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
Curated Video
Selenium WebDriver with Java - Basics to Advanced and Frameworks - Practice Exercise - Cisco Interview Question on Arrays
This video presents a practice exercise on arrays. This clip is from the chapter "Java Object Oriented Programming System (OOPS) Basic for Selenium Part - 1" of the series "Selenium WebDriver with Java - Basics to Advanced and...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Activity-Linear Algebra Module Python
In this video, we will cover activity-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...
msvgo
Evaluating Determinants
It explains how to evaluate the determinants of order 3 with the help of examples.
Zach Star
The algorithm that started google
This video goes over the very basics of the PageRank algorithm and how a google search works. The video is oversimplified and doesn't cover everything of course but note this was the was first algorithm used by Google. Now they use much...
Curated Video
The Risks and Rewards of Launching a New Product: An Introduction to Ansoff's Matrix
The video discusses the importance of businesses being aware of the risks and challenges associated with launching a new product or service onto the market. The speaker explains Ansoff's matrix, which outlines the level of risk that...
APMonitor
Solve Linear Equations with Excel
Excel MMULT and MINVERSE functions are used to solve systems of linear equations such as A * x = b by inverting A and multiplying by the right hand side (x = A^-1 * b).