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Python for Machine Learning - The Complete Beginners Course - Introduction - Optional: Setting Up Python and ML Algorithms Implementation
In this video, we will get a quick section introduction about the process of setting up the Python environment and implementing ML algorithms that will be covered in the upcoming videos. This clip is from the chapter "Optional: Setting...
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Python for Machine Learning - The Complete Beginners Course - Implementation Steps
In this video, you will learn the implementation steps. This clip is from the chapter "Classification Algorithms: Logistic Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will...
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Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Importing Required Libraries
In this video, you will learn how to import the required libraries. This clip is from the chapter "Classification Algorithms: K-Nearest Neighbors" of the series "Python for Machine Learning - The Complete Beginner's Course".In this...
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Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Feature Scaling
In this video, you will learn about feature scaling. This clip is from the chapter "Classification Algorithms: K-Nearest Neighbors" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will...
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Python for Machine Learning - The Complete Beginners Course - Exploring the Dataset
In this video, you will learn how to explore the dataset. This clip is from the chapter "Classification Algorithms: Decision Tree" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will...
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Machine Learning Random Forest with Python from Scratch - Past, Present, and Future of Machine Learning
This lecture illustrates why machine learning has started evolving recently and the future that beholds machine learning.
This clip is from the chapter "Introduction to the Course" of the series "Machine Learning: Random Forest with...
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Reinforcement Learning and Deep RL Python Theory and Projects - Loading and Understanding the Environment
This video explains about loading and understanding the environment. This clip is from the chapter "Stable Baselines Cartpole Solution" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses...
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Probability Statistics - The Foundations of Machine Learning - Applying Entropy - Coding Decision Trees for Machine Learning
In this video, you will learn how to apply Entropy by coding decision trees for machine learning. This clip is from the chapter "Applications to the Real World" of the series "Probability / Statistics - The Foundations of Machine...
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Data Structures and Algorithms The Complete Masterclass - Performance Analysis
This video explains the concept of performance analysis in data structure. This clip is from the chapter "Algorithm: Sorting Elementary" of the series "Data Structures and Algorithms: The Complete Masterclass".This section introduces you...
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Spring Framework Master Class - Java Spring the Modern Way - Step 13 - Autowiring in Depth - @Qualifier Annotation
This video demonstrates how to work with the @Qualifier annotation. This clip is from the chapter "Spring Level 2 - Spring Framework in Depth" of the series "Spring Framework Master Class - Java Spring the Modern Way".This section...
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SSL Complete Guide 2021: HTTP to HTTPS - Diffie Hellman Algorithm
In this video, we'll learn about the Diffie Hellman algorithm. This clip is from the chapter "SSL, TLS, and HTTPS" of the series "SSL Complete Guide 2021: HTTP to HTTPS".In this section, we'll learn about SSL, TLS, and HTTPS.
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SSL Complete Guide 2021: HTTP to HTTPS - How TLS Session is Established
In this video, we'll learn how TLS session is established. This clip is from the chapter "SSL, TLS, and HTTPS" of the series "SSL Complete Guide 2021: HTTP to HTTPS".In this section, we'll learn about SSL, TLS, and HTTPS.
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Python for Machine Learning - The Complete Beginners Course - Merging Datasets into One Dataframe
In this video, you will learn how to merge datasets into one dataframe. This clip is from the chapter "Recommender System" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will cover the...
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Python for Machine Learning - The Complete Beginners Course - Importing the Dataset
In this video, you will learn how to import the dataset. This clip is from the chapter "Clustering" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, you will learn about clustering.
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Deep Learning CNN Convolutional Neural Networks with Python - Shift Scale Rotation Invariance
This video explores shift scale rotation invariance. This clip is from the chapter "Object Detection" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on the methods of object detection.
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Deep Learning CNN Convolutional Neural Networks with Python - DNN Training Parameters
This video explains the DNN training parameters. This clip is from the chapter "Deep Neural Network Overview" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on the overview of the deep...
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Python for Machine Learning - The Complete Beginners Course - Introduction to Classification
In this video, we will have a quick introduction to classification. This clip is from the chapter "Classification Algorithms: K-Nearest Neighbors" of the series "Python for Machine Learning - The Complete Beginner's Course".In this...
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Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN Gradient Descent Exercise Solution
In this video, we will cover DNN gradient descent exercise solution. 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...
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Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: Training DNN Animation
In this video, we will cover training DNN animation. 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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Machine Learning Random Forest with Python from Scratch - Outliers
Let's look at outliers, the data points of a dataset that differ from others and are usually excluded by visualizing a dataset. This clip is from the chapter "Introduction to Machine Learning" of the series "Machine Learning: Random...
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Reinforcement Learning and Deep RL Python Theory and Projects - Pros and Cons
This video talks about the pros and cons of SARSA. This clip is from the chapter "SARSA (State–Action–Reward–State–Action)" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on SARSA...
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Dive Into Ansible - From Beginner to Expert in Ansible - Section 1 and 2 Quiz
This video presents quick quiz questions to test what you have learned from sections 1 and 2. This clip is from the chapter "Setting up of the Lab Environment and Course Resource" of the series "Dive Into Ansible - From Beginner to...
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Complete Modern C++ - Lambda Expressions Capture List - Part I
This video introduces the capture list. This clip is from the chapter "Lambda Expressions (C++11)" of the series "Complete Modern C++".In this section, we will investigate callbacks and lambda expressions.
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Java Programming for Complete Beginners - Java 16 - Step 04 - Java Modularization - 01 - Building Service and Consumer
In this lesson, we will build a simple application with modularization. This clip is from the chapter "Java New Features - Java 10 to Java 16" of the series "Java Programming for Complete Beginners - Java 16".This section focuses on the...