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Python In Practice - 15 Projects to Master Python - Finding TF and IDF in Extracted Features from Text Data: Text Analytics
This video explains finding TF and IDF in extracted features from text data, that is, text analytics. This clip is from the chapter "Artificial Intelligence" of the series "Python in Practice - 15 Projects to Master Python".This section...
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Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Methods: Clustering
In this video, we will cover clustering. 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 cover...
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Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Unsupervised Learning
In this video, we will cover unsupervised learning. 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 this section, we...
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Selenium WebDriver with Java - Basics to Advanced and Frameworks - Using Inheritance in Java
This video explains how to use inheritance in Java. 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...
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AWS Certified Data Analytics Specialty 2021 - Hands-On! - AWS Glue Studio
This video focuses on AWS Glue studio. This clip is from the chapter "Domain 3: Processing" of the series "AWS Certified Data Analytics Specialty 2021 "Hands-On!".In this section, we will complete our “order history app†example by...
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Data Science and Machine Learning (Theory and Projects) A to Z - Random Variables: Random Variables Examples
In this video, we will cover random variables examples. This clip is from the chapter "Basics for Data Science: Mastering Probability and Statistics in Python" of the series "Data Science and Machine Learning (Theory and Projects) A to...
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Data Science and Machine Learning (Theory and Projects) A to Z - Feature Engineering: Categorical Features
In this video, we will cover categorical features. 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...
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Deep Learning - Deep Neural Network for Beginners Using Python - Visualization and Results
In this video, we will work on visualization and results. This clip is from the chapter "Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will dive deeper into deep learning.
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Deep Learning - Deep Neural Network for Beginners Using Python - Training (NN Implementation)
In this video, you will learn how to train our neural network. This clip is from the chapter "Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will dive deeper into deep...
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Deep Learning - Deep Neural Network for Beginners Using Python - Implementing Logistic Regression
In this video, you will learn how to implement logistic regression. This clip is from the chapter "Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will dive deeper into...
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Deep Learning - Deep Neural Network for Beginners Using Python - Final Project Part 1
In this first video, we will understand our project goals. Next, we will explore the Iris dataset, then learn how to update and split the data. This clip is from the chapter "Final Project" of the series "Deep Learning - Deep Neural...
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Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Classification Training Process and Prediction Probabilities
In this video, we will cover classification training process and prediction probabilities. This clip is from the chapter "Deep learning: Artificial Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and...
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Data Science and Machine Learning (Theory and Projects) A to Z - Transfer Learning: Why Transfer Learning
In this video, we will understand why transfer learning. 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...
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Data Science and Machine Learning (Theory and Projects) A to Z - Process of Learning from Data: Supervised Learning
In this video, we will cover supervised learning. 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...
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Data Science and Machine Learning (Theory and Projects) A to Z - Data Preparation and Preprocessing: Handling Text Data
In this video, we will cover handling text data. 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...
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Using ChatGPT in Google Sheets: Advanced Features and Variables
In this lesson, we explore the advanced features and variables that can be adjusted in Google Sheets when using the ChatGPT add-on. We will learn how to adjust prompts, values, and temperature according to our needs and how to use the...
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Using Prompt Engineering and Extra Features in Chat GPT with Excel
In this lesson, we will explore how to use prompt engineering and extra features in Chat GPT with Excel. We will learn how to adjust variables and features to receive specific responses, how to create taglines for different countries,...
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Deimatic Displays: The Surprising Defense Mechanisms of Animals
In this video, we explore the fascinating world of deimatic behavior in animals. Deimatic behavior involves the use of surprise and dramatic displays, such as eyespots, to startle and deter predators. This video provides insights into...
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The Complete React Developer Course (with Hooks and Redux) - Installing Node.js & Yarn
The last thing you need to install is Node.js. You'll be using Node.js to create web servers, compile files, and much more! This clip is from the chapter "Setting up Your Environment" of the series "The Complete React Developer Course...
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Vim Masterclass - Course Overview
This video provides an overview of the course. This clip is from the chapter "Course Introduction" of the series "Vim Masterclass".This section introduces the course.
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Java Interview Guide : 200+ Interview Questions and Answers - Java New Features - Java 5, 6, 7 and 8
New Features: Java New Features - Java 5, 6, 7 and 8 This clip is from the chapter "New Features" of the series "Java Interview Guide : 200+ Interview Questions and Answers".In this section, you will learn the new features of Java.
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Python for Deep Learning - Build Neural Networks in Python - Components of Convolutional Neural Networks
In this video, you will learn about the components of Convolutional Neural Networks. This clip is from the chapter "Convolutional Neural Networks (CNN)" of the series "Python for Deep Learning — Build Neural Networks in Python".In this...
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Raspberry Pi For Beginners - 2022 Complete Course - Introduction - Create a Web Application on Your Raspberry Pi with Flask and Python
This video provides an introduction to the section. This clip is from the chapter "Create a Web Application on Your Raspberry Pi with Flask and Python" of the series "Raspberry Pi for Beginners - 2022 Complete Course".This section...
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Practical Data Science using Python - Naive Bayes - Employee Attrition Case Study
This video explains Naive Bayes - employee attrition case study. This clip is from the chapter "Naive Bayes Probability Model" of the series "Practical Data Science Using Python".This section explains Naive Bayes probability model –...