Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: Calculating Number of Weights of DNN
In this video, we will cover calculating number of weights of DNN. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: Batch Minibatch Stochastic
In this video, we will cover batch minibatch stochastic.
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Network Architecture: Why Convolution
In this video, we will understand why convolution. 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,...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - RNN Implementation: Language Modelling Next Word Prediction Python 2
In this video, we will cover language modelling next word prediction Python 2. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: Notations
In this video, we will cover notations. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: Introduction to Module
In this video, we will cover an introduction to module. 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,...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: Infinite Memory Architecture Solution
In this video, we will cover infinite memory architecture 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: Fixed Length Memory Model Exercise Solution Part 02
In this video, we will cover fixed length memory model exercise solution part 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)...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: Deep RNNs Solution
In this video, we will cover Deep RNNs 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 - RNN Architecture: Deep RNNs Exercise
In this video, we will cover Deep RNNs 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Project I_ Book Writer: Modelling RNN Model Text Generation
In this video, we will cover modelling RNN model text generation. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in RNN: Example Setup
In this video, we will cover example setup. 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 BackwardPass 5
In this video, we will cover implementation in NumPy BackwardPass 5. 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 - Vanishing Gradients in RNN: GRU Optional
In this video, we will cover GRU Optional. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Vanishing Gradients in RNN: Attention Model Optional
In this video, we will cover attention model optional. 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,...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Vanishing Gradients in RNN: Attention Model
In this video, we will cover attention model. 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 - Transfer Learning: Practical Tips
In this video, we will cover practical tips. 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
Histograms and Frequency Density
This video shows the process for solving the problem presented in IGCSE A June 2018 paper 2H Q20, which involves histograms and frequency density. Students will understand how to interpret a histogram that shows information about the...
Curated Video
Solving Absolute Value Conjunction Inequalities
In this video, the teacher explains how to solve absolute value conjunction inequalities by writing two different inequalities. The concept of absolute value is introduced, and the process of solving absolute value equations is...
Curated Video
Comparing Variability: Medians and Interquartile Ranges
In this video, the teacher explains how to compare the variability in weights of professional baseball and soccer players using medians and interquartile ranges. They demonstrate that while baseball players are heavier on average, soccer...
Curated Video
Ensemble Machine Learning Techniques 2.4: Ensemble Learning for Regression
This video aims to teach the viewer how to use Ensemble Learning for Regression. • We go into the details of averaging • We see examples for averaging in real life • Look at weighted averaging
Looking Glass Universe
What is the Fourier Transform?
In this video, well look at the fourier transform from a slightly different perspective than normal, and see how it can be used to estimate functions.
Curated Video
Metals Weight (Use the four operations to solve word problems involving measurements expressed in fractional or decimal numbers and requiring conversion of larger units to smaller units)
Lee is working in the materials laboratory. He measures the weights of various small pieces of metal. The table shows the sheet where he recorded the different weights. What is the total weight in ounces of the metals that were measured...
Professor Dave Explains
Practice Problem: Torque on a Mobile
You had a baby! Hooray! Now it's time to stop building ramps and pulleys and it's time to start building baby stuff. You love astronomy so you decide to make a mobile of the solar system. But in order to get everything to balance out, we...