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...
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 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 Video6:10
Curated Video

Learn and Master C Programming - Let's Implement a Variadic Function in C - Technique #1

Higher Ed
We will learn to implement a function called "Sum" that sums up all arguments passed to it using a variable number of arguments while passing the count as the first argument on the list. This clip is from the chapter "Advanced Topics" of...
Instructional Video9:05
Packt

Advanced Computer Vision Projects 2.3: Finding Plate Characters

Higher Ed
In this video, we take a pass at finding characters potentially belonging to license plates. • Use contours to find character candidates • Filter contours based on geometric criteria • Identify possible plate locations based on characters
Instructional Video6:06
Curated Video

Predictive Analytics with TensorFlow 3.4: Data Model in TensorFlow

Higher Ed
The data model in TensorFlow is represented by tensors. Without using complex mathematical definitions, we can say that a tensor identifies a multidimensional numerical array. • Create tensors • Define the ranks, shape and data type •...
Instructional Video6:41
Curated Video

High Performance Scientific Computing with C 1.6: Monte Carlo Methods

Higher Ed
How can we use random numbers to solve problems? • Learn why randomness is useful • See how we can solve integrals with random numbers • See how the accuracy of Monte Carlo methods scales
Instructional Video15:40
Curated Video

Predictive Analytics with TensorFlow 9.4: An LSTM Predictive Model for Sentiment Analysis

Higher Ed
Sentiment analysis is one of the most widely performed tasks in NLP. An LSTM network can be used to classify short texts into desired categories–that is, classification problems. For example, a set of tweet texts can be categorized as...
Instructional Video15:34
Curated Video

Cloud Native Development on Azure with Java 1.3: Set Up the Environment for Building a Cloud Native Application

Higher Ed
This video will guide you through the steps of deploying the prerequisites and setting up your development environment using an Azure virtual machine. • Use an Azure VM • Install JDK, Apache Maven, and Azure CLI
Instructional Video5:05
Packt

Advanced Computer Vision Projects 1.2: Image Captioning Introduction

Higher Ed
We cover image classification vs. captioning and touch on recurrent neural networks with long-short-term-memory. • Understand that captioning is an extension of classification to generate more human friendly image labelling • Learn about...
Instructional Video4:34
Curated Video

Predictive Analytics with TensorFlow 3.2: TensorFlow Computational Graph

Higher Ed
When thinking of execution of a TensorFlow program we should be familiar with a graph creation and a session execution. Basically the first one is for building the model and the second one is for feeding the data in and getting the...
Instructional Video9:49
Curated Video

Predictive Analytics with TensorFlow 8.5: CNN Model for Emotion Recognition

Higher Ed
We will first train the CNN model based on the dataset from Kaggle and then we will test that model to test a human face to predict one of the emotions. In this video, we show how to develop a CNN for emotion prediction from facial...
Instructional Video6:22
Curated Video

Predictive Analytics with TensorFlow 10.2: Factorization Machines for Recommendation Systems

Higher Ed
We will look at two examples for developing a more robust recommendation systems using FM. We will also see FM and their applications in the cold-start recommendation problem. • Understand the factorization machines • Look at the cold...
Instructional Video3:56
Curated Video

Predictive Analytics with TensorFlow 8.3: Tuning CNN Hyperparameters

Higher Ed
In this video, we will tune the CNN hyperparameters. • Tune the CNN hyperparameters
Instructional Video5:34
Curated Video

Predictive Analytics with TensorFlow 8.1: CNNs and the Drawbacks of Regular DNNs

Higher Ed
CNNs are a type of feedforward neural network in which the connectivity pattern between its neurons is based on the animal visual cortex. We will also see CNN architecture and convolution operations. • Look at CNNs and drawbacks of...
Instructional Video4:30
Curated Video

Ensemble Machine Learning Techniques 2.3: Ensemble Learning for Classification

Higher Ed
In this video, we will use python to write a simple ensemble learning model for classification. • We will use Jupyter Notebook to execute our code • Use Iris dataset to perform classification • Use hard voting and soft voting for...
Instructional Video3:40
Curated Video

Predictive Analytics with TensorFlow 3.3: TensorFlow Programming Model

Higher Ed
The TensorFlow programming model signifies how to structure your predictive models. • Look at the steps for structuring the model
Instructional Video12:23
Curated Video

Hands-On Unity 2018.x Game Development for Mobile (Video 10)

Higher Ed
Ready to take your game development skills to the next level by deploying your games to mobile platforms? With the boom in the mobile game development space, there has never been a better time! This course will give you the necessary...
Instructional Video11:32
Curated Video

Mastering Tableau 2018.1, Second Edition 11.1: Data Visualization Best Practices for Effective Dashboards

Higher Ed
In this video, we’ll see the best practices that we can use to create effective dashboards. • Best practices for creating effective dashboards • Implement best practices for effective dashboards
Instructional Video9:43
Curated Video

Predictive Analytics with TensorFlow 6.5: Using Word2vec for Sentiment Analysis

Higher Ed
We will see how we can improve the previous predictive model with minimum effort using TF-IDF. • Use Word2vec for doing sentiment analysis
Instructional Video4:13
Curated Video

Predictive Analytics with TensorFlow 6.2: Transformers and Estimators

Higher Ed
We will get a brief explanation of transformers and estimators. We will also look at different types of transformers and estimators. • Look at the different types of transformers • Look at the different types of estimators