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Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Machine Learning Model
In this video, we will cover machine learning model. 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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Data Science and Machine Learning (Theory and Projects) A to Z - Multiple Random Variables: Conditioning Independence
In this video, we will cover conditioning independence.
Curated Video
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 - 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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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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Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Methods: Classification
In this video, we will cover classification. 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 - Deep Neural Networks and Deep Learning Basics: Discriminative Versus Generative Learning
In this video, we will cover discriminative versus generative 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...
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Machine Learning Random Forest with Python from Scratch - Pros and Cons of Random Forest
In this video, we will look at the benefits and limitations of Random Forest and the complexities involved in decision-making using Random Forest. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine...
Professor Dave Explains
Basidiomycota Part 1: Ustilaginomycotina and Pucciniomycotina (Smuts and Rusts)
Now that we have a general overview of fungal taxonomy covered, it's time to start investigating the different fungal phyla. The first one we will investigate is the most important one, basidiomycota. There are three subphyla in this...
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Python for Machine Learning - The Complete Beginners Course - What Is Jupyter?
In this video, we will understand Jupyter Notebook. This clip is from the chapter "Optional: Setting Up Python and ML Algorithms Implementation" 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 - Steps of the Elbow Method
In this video, we will cover the steps of the elbow method. 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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Python for Machine Learning - The Complete Beginners Course - Root Mean Squared Error in Python
In this video, we will cover root mean squared error in Python. This clip is from the chapter "Multiple Linear Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will cover...
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Python for Machine Learning - The Complete Beginners Course - Logistic Regression Versus Linear Regression
In this video, we will cover logistic regression versus linear regression. This clip is from the chapter "Classification Algorithms: Logistic Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In...
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Python for Machine Learning - The Complete Beginners Course - K-Nearest Neighbors Algorithm
In this video, we will cover the K-Nearest Neighbors algorithm. 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,...
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Python for Machine Learning - The Complete Beginners Course - Introduction to Regression
In this video, we will have a quick introduction to regression. This clip is from the chapter "Simple Linear Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will cover simple...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Implementing Python in Jupyter
In this video, you will learn how to implement Python in Jupyter. This clip is from the chapter "Optional: Setting Up Python and ML Algorithms Implementation" of the series "Python for Machine Learning - The Complete Beginner's...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Importing Libraries and Datasets - Classification Algorithms: Decision Tree
In this video, you will learn how to import libraries and datasets. 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...
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Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Exploring the Dataset
In this video, we will first explore our dataset, then learn how to import and read our dataset in Python. This clip is from the chapter "Multiple Linear Regression" of the series "Python for Machine Learning - The Complete Beginner's...
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Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Encoding Categorical Data - Multiple Linear Regression
In this video, you will learn how to encode categorical data. This clip is from the chapter "Multiple Linear Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will cover multiple...
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Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Distribution of the Data
In this video, you will learn distribution of the data. This clip is from the chapter "Simple Linear Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will cover simple linear...
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Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Creating a Linear Regression Object
In this video, you will learn how to create a linear regression object. This clip is from the chapter "Simple Linear Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will cover...
Curated Video
Python for Machine Learning - The Complete Beginners Course - How Does Linear Regression Work?
In this video, we will understand how linear regression works. This clip is from the chapter "Simple Linear Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will cover simple...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Histogram Showing Number of Ratings
In this video, you will learn how a histogram shows the number of ratings. 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...