Instructional Video10:10
Curated Video

Discuss the importance of data : Basics of decision trees

Higher Ed
From the section: Simple Decision trees. In this section, we will start with the basic theory of decision tree then we cover data pre-processing topics like missing value imputation, variable transformation and Test-Train split. In the...
Instructional Video10:11
Curated Video

Design a computer system using tree search and reinforcement learning algorithms : Creating an Agent to Solve the MAB Problem Using Python and Tensorflow

Higher Ed
From the section: The Multi-Armed Bandit. In this section, we will learn about the basics and look at one of the most foundational concepts in Reinforcement Learning – The Multi-Armed Bandit We construct a model of a MAB environment from...
Instructional Video11:36
Curated Video

Describe computer programming : Common Data Types

Higher Ed
From the section: Common Coding Concepts.This section will cover common coding concepts such as Scratch setup, bugs, pseudocode, decomposition, commenting and many more. Common Coding Concepts: Common Data Types
Instructional Video25:36
Curated Video

Describe computer programming : You Can Code! Part 2

Higher Ed
From the section: You can code!. This section will help you discover some interesting facts about coding. You can code!: You Can Code! Part 2 • Get the synopsis about the Tuple • Learn about the benefits of Tuple • Learn about the...
Instructional Video7:10
Curated Video

Describe computer programming : You Can Code! Part 1

Higher Ed
From the section: You can code!. This section will help you discover some interesting facts about coding. You can code!: You Can Code! Part 1 • Create a simple list with names and another with numbers • Explain the concept of indexing •...
Instructional Video12:20
Curated Video

Create a computer vision system using decision tree algorithms to solve a real-world problem : Introduction: What are Artificial Neural Networks and how do they learn?

Higher Ed
From the section: Artificial Neural Networks. In this section, we’ll cover Bayes Theorem, Naive Bayes, SVM and SVC to classify data. Artificial Neural Networks: Introduction: What are Artificial Neural Networks and how do they learn?
Instructional Video8:09
Curated Video

Create a computer vision system using decision tree algorithms to solve a real-world problem : [Activity] Support Vector Classifiers in Action

Higher Ed
From the section: Machine Learning: Part 2. In this section, we’ll cover Bayes Theorem, Naive Bayes, SVM and SVC to classify data. Machine Learning: Part 2: [Activity] Support Vector Classifiers in Action
Instructional Video7:52
Curated Video

Predictive Analytics with TensorFlow 9.1: Using BRNN for Image Classification

Higher Ed
We will first provide some contextual information about RNNs. We will see how to implement a BRNN implementation example using the TensorFlow library. The example is using the MNIST database of handwriting. • Look at contextual...
Instructional Video1:13
Packt

Data transmission : Physical versus logical topology

Higher Ed
From the section: Introduction to Computer Networks (ICND1). This Section introduces Computer Networks. This includes lectures on Physical Components, Topology, Speed etc. Introduction to Computer Networks (ICND1): Physical versus...
Instructional Video5:25
Curated Video

Evaluate the impact of an AI application used in the real world. (case study) : Working with X-Ray images: Case Study - Part 6

Higher Ed
From the section: CNN-Industry Live Project: Find Medical Abnormalities and Save Life. This section includes a CNN-Industry live project on working with X-Ray images. CNN-Industry Live Project: Find Medical Abnormalities and Save Life:...
Instructional Video4:07
Curated Video

Evaluate the impact of an AI application used in the real world. (case study) : Working with Flower Images: Case Study - Part 1

Higher Ed
From the section: CNN-Industry Live Project: Playing With Real World Natural Images. This section includes a live project of working with flower images. CNN-Industry Live Project: Playing with Real World Natural Images: Working with...
Instructional Video8:04
Curated Video

Call a function : String Manipulation Functions

Higher Ed
From the section: Intro to PHP Programming for Web Development. In this section, we’ll learn the basics of PHP programming. Intro to PHP Programming for Web Development: String Manipulation Functions
Instructional Video6:15
Curated Video

Create a computer vision system using decision tree algorithms to solve a real-world problem : Support Vector Machines (SVM) and Support Vector Classifiers (SVC)

Higher Ed
From the section: Machine Learning: Part 2. In this section, we’ll cover Bayes Theorem, Naive Bayes, SVM and SVC to classify data. Machine Learning: Part 2: Support Vector Machines (SVM) and Support Vector Classifiers (SVC)
Instructional Video2:17
Curated Video

Java 11 Programming for Beginners 3.3: Inheritance — The Non-Taxable Kind

Higher Ed
Showcase the heaviest concept in OOP by example. • Build a second bot by leveraging the first • Go through theory
Instructional Video10:45
Curated Video

Predictive Analytics with TensorFlow 5.1: Using K-means for Predictive Analytics

Higher Ed
This video will have a brief introduction to the unsupervised machine learning technique. We will also look at k-means for predictive analytics. • Understand the concept of clustering • See how k-means work • Use k-means for predicting...
Podcast1:07:49
NASA

‎Houston We Have a Podcast: Her Passion for STEM

Pre-K - Higher Ed
Kris Brown and Emily Calandrelli describe the importance of inspiring young women to pursue an interest in science, technology, engineering and math. HWHAP Episode 232.
Instructional Video3:50
Curated Video

Predictive Analytics with TensorFlow 7.4: Deep Belief Networks

Higher Ed
While weights of an MLP are initialized randomly, a DBN uses a greedy layer-by-layer pretraining algorithm to initialize the network weights through probabilistic generative models composed of a visible layer and multiple layers of...
Instructional Video6:59
Curated Video

Predictive Analytics with TensorFlow 7.2: Fine-tuning DNN Hyperparameters

Higher Ed
First, we will see DNN performance analysis. Next, we will tune the DNN hyperparameters. • Do DNN performance analysis • Tune the DNN hyperparameters
Instructional Video3:18
Packt

Course Introduction - Data Structures and Algorithms The Complete Masterclass

Higher Ed
This video introduces you to the course. This clip is from the chapter "Course Introduction" of the series "Data Structures and Algorithms: The Complete Masterclass".This section provides an introduction to the course.
Instructional Video8:59
Curated Video

Create a computer vision system using decision tree algorithms to solve a real-world problem : [Activity] Naive Bayes in Action

Higher Ed
From the section: Machine Learning: Part 2. In this section, we’ll cover Bayes Theorem, Naive Bayes, SVM and SVC to classify data. Machine Learning: Part 2: [Activity] Naive Bayes in Action
Instructional Video2:56
Curated Video

Learning D3.JS 5.0 2.4: Creating Circles and Ellipses

Higher Ed
In this video, we will learn how to create circles and ellipses. • Code a circle and view it in the browser • Fix the problem with viewing only one quarter of the circle • Code an ellipse and view it correctly
Instructional Video7:05
Curated Video

Tips, Tricks, and Techniques for Node.js Development 5.2: Creating a Child Process

Higher Ed
In this video, we will learn how to execute code in a child process. • Show the different ways of creating a child process • Create a child.js script • Show communication between child processes
Instructional Video6:22
Packt

Introduction to computer hardware and software : Form Factors

Higher Ed
From the section: Motherboards. In this section, we look into motherboard features such as Chipsets and how to install. Motherboards, power supplies, and cases are surprisingly interchangeable due to industry standards called form...
Instructional Video10:38
Curated Video

Discuss the importance of data : Pruning a tree in Python

Higher Ed
From the section: Simple Decision trees. In this section, we will start with the basic theory of decision tree then we cover data pre-processing topics like missing value imputation, variable transformation and Test-Train split. In the...