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Data Science Model Deployments and Cloud Computing on GCP - Build Automation Tools
This video explains how to build automation tools, which are supporting tools that can execute a number of different tasks for developers creating an application. This clip is from the chapter "Web Developer Tools" of the series "Web...
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Data Science Model Deployments and Cloud Computing on GCP - Special Mention - AngularJS Versus Angular
This video explains the difference between AngularJS and Angular, which is written using JavaScript and TypeScript simultaneously. This clip is from the chapter "Libraries and Front-End Frameworks" of the series "Web Development Concepts...
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Data Science Model Deployments and Cloud Computing on GCP - CSS Frameworks and Bootstrap
This video explains CSS frameworks and Bootstrap. This clip is from the chapter "Libraries and Front-End Frameworks" of the series "Web Development Concepts for Everyone".This video explains libraries and front-end frameworks.
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Data Science Model Deployments and Cloud Computing on GCP - Supersets and TypeScript
This video explains supersets, which are a language that contains all the features of a given language, but then is expanded or enhanced to include other features as well. TypeScript is a superset of JavaScript developed and maintained...
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Data Science Model Deployments and Cloud Computing on GCP - Introduction to Programming Types
This video introduces you to different programming types such as numbers, strings, and Booleans. This clip is from the chapter "Programming Languages" of the series "Web Development Concepts for Everyone".In this section, you are going...
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Data Science Model Deployments and Cloud Computing on GCP - Introduction-GCP - Serverless Spark
This video provides an introduction to the section. This clip is from the chapter "Dataproc Serverless PySpark" of the series "Data Science Model Deployments and Cloud Computing on GCP".In this section, you will learn about Dataproc, a...
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Vue.js 3 and Firebase for Beginners - Views and Routes
In this video, the author provides insights into the views and routes folders, along with their specific locations within the code structure. This information will help you navigate the code structure effectively and streamline your...
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Linux Crash Course for Beginners - 2023 - Basic Shell Scripts
In this video, you will learn some basics commands of shell scripts such as echo, cut, awk, and more.
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Linux Crash Course for Beginners - 2023 - File Display Commands
In this video, you will learn all the commands that can be used to display file content such as cat, less, more, head, tail, vi.
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Linux Crash Course for Beginners - 2023 - File Ownership Commands
In this video, you will learn how files and directories are owned and how we can change their ownership.
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Linux Crash Course for Beginners - 2023 - File Permissions
In this video, you will learn how we can change the file permissions.
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Linux Crash Course for Beginners - 2023 - Course Overview
In this video, we will have a look at the course syllabus.
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Learn Java from Scratch - A Beginner's Guide - Step 00 – Step-By-Step Problem Solving with Programming
We have successfully installed Java. Let's take a look at the next step, which is problem solving.
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Fundamentals of Neural Networks - Bi-Directional RNN
Bidirectional recurrent neural networks (BRNN) connect two hidden layers of opposite directions to the same output. BRNNs are especially useful when the context of the input is needed. For example, in handwriting recognition, the...
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Fundamentals of Neural Networks - Gated Recurrent Unit (GRU)
Gated recurrent units (GRUs) are a gating mechanism in recurrent neural networks. GRUs have been shown to exhibit better performance on certain smaller and less frequent datasets. This clip is from the chapter "Recurrent Neural Networks"...
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Fundamentals of Neural Networks - Backward Propagation Through Time
Backpropagation through time (BPTT) is a gradient-based technique for training certain types of recurrent neural networks. It can be used to train Elman networks. The algorithm was independently derived by numerous researchers. This clip...
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Fundamentals of Neural Networks - Forward Propagation in RNN
The forward propagation in an RNN makes a few assumptions: 1) We assume the hyperbolic tangent activation function for the hidden layer. 2) We assume that the output is discrete as if the RNN is used to predict words or characters. This...
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Fundamentals of Neural Networks - VGG16
This video explains VGG16 which is a convolutional neural network model proposed by K. Simonyan and A. Zisserman from the University of Oxford in the paper "Very Deep Convolutional Networks for Large-Scale Image Recognition". This clip...
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Fundamentals of Neural Networks - Tensor and Matrix
This video explains what we mean by Tensor and Matrix. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural networks where you will start...
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Fundamentals of Neural Networks - Gradient Descent
This video explains the optimization problem using the gradient descent algorithm. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains artificial neural...
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Fundamentals of Neural Networks - Cross-Entropy Loss Function
This video explains the cross-entropy function, which is designed under the assumption that the variable you are trying to predict is binary. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in...
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Fundamentals of Neural Networks - Backward Propagation
This video explains backward propagation, which is defined by the optimization problem called the gradient descent algorithm. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This...
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Fundamentals of Neural Networks - Logistic Regression
This video explains logistic regression and specifically if the target here is discrete or binary. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...
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Fundamentals of Neural Networks - Linear Regression
This video explains statistical machine learning, where you will start with the linear regression model. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...