In this video, we will work on Anaconda installation for Windows, Mac, and Ubuntu.
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This clip is from the chapter "Optional: Setting Up Python and ML Algorithms Implementation" of the series "Python for Machine Learning - The...

Long short-term memory (LSTM) is an artificial recurrent neural network (RNN) architecture used in the field of deep learning. LSTM networks are well-suited to classifying, processing, and making predictions based on time series data...

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...

This video explains unsupervised learning, Principal Components Analysis (PCA), and clustering.
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This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of...

The second part of the tree-based methods explains random forests.
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This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical learning, sampling,...

This video explains the support vector machine called SVM and its introduction.
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This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical...

This video explains a lab session on Support Vector Machines or SVM.
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This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on linear regression,...

This video explains linear regression using an example of predicting fuel efficiency.
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This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on...

This video explains the foundation of the linear regression model, which is the very first approach to supervised learning.
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This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This...

This video explains one of the most basic forms of classification, which is the logistic regression model.
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This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the...

This video explains some basic notations in statistical learning, such as Xij.
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This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical...

In this video, you will learn how to visualize the dataset.
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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...

In this video, you will learn how to sort by title and rating.
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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...

In this video, you will learn how to set up Python.
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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...

In this video, you will learn how to manage directories in Jupyter Notebook.
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This clip is from the chapter "Optional: Setting Up Python and ML Algorithms Implementation" of the series "Python for Machine Learning - The...

In this video, we will have a quick introduction.
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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...

In this video, you will learn how to train the model.
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This clip is from the chapter "Classification Algorithms: Logistic Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this...

In this video, you will learn how to split data into train and test sets.
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This clip is from the chapter "Multiple Linear Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this...

In this video, you will learn about results prediction and confusion matrix.
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This clip is from the chapter "Classification Algorithms: K-Nearest Neighbors" of the series "Python for Machine Learning - The Complete Beginner's...

In this video, you will learn how to predict the test set results.
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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...

In this video, you will learn how to import libraries and datasets.
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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...

In this video, you will learn how to encode categorical data.
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This clip is from the chapter "Classification Algorithms: Decision Tree" of the series "Python for Machine Learning - The Complete Beginner's Course".In this...

In this video, we will cover hierarchical clustering.<br<br/>/>

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.

In this video, you will learn about frequency distribution.
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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...