National Parks Service
Acadia National Park - Floating Classroom: Accuracy
These videos compliment the variety of water quality programs that occur in Acadia National Park. For teachers looking for good background information on water quality or those looking to attend the Floating Classroom field trip, this...
Curated Video
Practical Data Science using Python - Central Limit Theorem
This video explains the Central Limit Theorem. This clip is from the chapter "Statistical Techniques" of the series "Practical Data Science Using Python".This section explains advanced visualizations using business applications.
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Fundamentals of Machine Learning - Welcome
This video explains the contents of the course. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical learning, sampling, and Bootstrap as well as...
Curated Video
Fundamentals of Machine Learning - Unsupervised Learning
This video explains unsupervised learning, Principal Components Analysis (PCA), and clustering. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical...
Curated Video
Fundamentals of Machine Learning - Support Vector Machine (SVM) - Lectures
This video explains the support vector machine called SVM and its introduction. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical learning, sampling,...
Curated Video
Fundamentals of Machine Learning - Support Vector Machine (SVM) - Labs
This video explains a lab session on Support Vector Machines or SVM. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on linear regression, ridge...
Curated Video
Fundamentals of Machine Learning - Basics in Statistical Learning
This video explains some basic notations in statistical learning, such as Xij. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical learning, sampling,...
Curated Video
Fundamentals of Machine Learning - Tree-Based Methods - Part 2
The second part of the tree-based methods explains random forests. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical learning, sampling, and...
Curated Video
Fundamentals of Machine Learning - Linear Regression - Labs
This video explains linear regression using an example of predicting fuel efficiency. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on linear...
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Fundamentals of Machine Learning - Linear Regression - Lectures
This video explains the foundation of the linear regression model, which is the very first approach to supervised learning. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains...
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Fundamentals of Machine Learning - Classification
This video explains one of the most basic forms of classification, which is the logistic regression model. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of...
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Fundamentals of Machine Learning - PCA
This video explains a lab session on Eigenfaces using PCA. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on linear regression, ridge regression,...
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Fundamentals of Machine Learning - Ridge
This video explains a lab session on Ridge regression, which holds a unique position in statistical machine learning. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various...
Curated Video
Fundamentals of Machine Learning - Logistic Regression
This video explains logistic regression with a little bit of mathematics behind it. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on linear...
Curated Video
Fundamentals of Machine Learning - Tree-Based Methods - Part 1
This part of the video explains decision tree. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical learning, sampling, and Bootstrap as well as support...
Curated Video
Fundamentals of Machine Learning - Going Beyond Linearity
This video explains going beyond linearity; specifically, we will look at a couple of interesting examples to improve the linear regression model to see if we can create models that are non-linear. This clip is from the chapter...
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Fundamentals of Machine Learning - Decision Tree
This video explains a lab session on a decision tree, getting dependencies, and how to create mock data. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab...
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Fundamentals of Machine Learning - Classification Metrics
This video explains classification metrics and will cover terminologies such as accuracy, specificity, sensitivity, and so on. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section...
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Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Machine Learning Overfitting Exercise Solution Regularization
In this video, we will cover machine learning overfitting exercise solution regularization. This clip is from the chapter "Deep learning: Artificial Neural Networks with Python" of the series "Data Science and Machine Learning (Theory...
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Fundamentals of Machine Learning - Sampling and Bootstrap
This video explains the two most famous and common procedures—cross-validation and Bootstrap. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical...
Curated Video
Fundamentals of Machine Learning - ROCAUC
In this final lab, you will learn about ROC-AUC (Receiver Operating Characteristic Curve-Area Under Curve). This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab...
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Fundamentals of Machine Learning - Random Forests
This video explains a lab session on random forests and a review of decision trees. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on linear...
Curated Video
Fundamentals of Machine Learning - Multilayer Perceptron (MLP)
This video explains a lab session on neural networks and Multilayer Perceptron (MLP) models. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on linear...
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Fundamentals of Machine Learning - CNN
This video continues the lab from neural networks and will have a look at convolutional neural networks. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab...