Instructional Video8:16
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Building Machine Learning Model from Scratch: Linear Regression from Scratch- Part 1

Higher Ed
In this video, we will cover linear regression from scratch- part 1. 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...
Instructional Video51:45
Curated Video

Fundamentals of Machine Learning - Unsupervised Learning

Higher Ed
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...
Instructional Video37:51
Curated Video

Fundamentals of Machine Learning - Tree-Based Methods - Part 2

Higher Ed
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...
Instructional Video22:10
Curated Video

Fundamentals of Machine Learning - Support Vector Machine (SVM) - Lectures

Higher Ed
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,...
Instructional Video10:04
Curated Video

Fundamentals of Machine Learning - Support Vector Machine (SVM) - Labs

Higher Ed
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...
Instructional Video20:45
Curated Video

Fundamentals of Machine Learning - Linear Regression - Labs

Higher Ed
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...
Instructional Video39:02
Curated Video

Fundamentals of Machine Learning - Linear Regression - Lectures

Higher Ed
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...
Instructional Video22:39
Curated Video

Fundamentals of Machine Learning - Classification

Higher Ed
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...
Instructional Video42:41
Curated Video

Fundamentals of Machine Learning - Basics in Statistical Learning

Higher Ed
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,...
Instructional Video11:57
Curated Video

Practical Data Science using Python - Regression Models and Performance Metrics

Higher Ed
This video explains regression models and performance metrics. This clip is from the chapter "Machine Learning" of the series "Practical Data Science Using Python".This section explains machine learning.
Instructional Video18:43
Curated Video

Practical Data Science using Python - Linear Regression OLS Assumptions and Testing

Higher Ed
This video explains linear regression OLS assumptions and testing. This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.
Instructional Video3:31
Curated Video

Practical Data Science using Python - Linear Regression Model Optimization

Higher Ed
This video explains linear regression model optimization. This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.
Instructional Video16:19
Curated Video

Practical Data Science using Python - Linear Regression Model Building

Higher Ed
This video explains linear regression model building. This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.
Instructional Video13:17
Curated Video

Practical Data Science using Python - Classification Problems and Performance Metrics

Higher Ed
This video explains classification problems and performance metrics. This clip is from the chapter "Machine Learning" of the series "Practical Data Science Using Python".This section explains machine learning.
Instructional Video4:18
Curated Video

Python In Practice - 15 Projects to Master Python - How Machines Learn

Higher Ed
This video explains how machines learn. This clip is from the chapter "Machine Learning with Python" of the series "Python in Practice - 15 Projects to Master Python".This section focuses on machine learning with Python.
Instructional Video9:40
Packt

Fundamentals of Neural Networks - Linear Regression

Higher Ed
This video explains statistical machine learning, where you will start with the linear regression model. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...
Instructional Video14:29
Curated Video

Fundamentals of Neural Networks - Lab 2 - Introduction to TensorFlow – Remove the Throat-Clearing Sound in the Start of the Video

Higher Ed
This video demonstrates some basic operations in TensorFlow such as objects and we will apply some mathematical operations to the Tensor objects. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in...
Instructional Video35:44
Packt

Fundamentals of Neural Networks - Lab 1 - Introduction to Python

Higher Ed
This video demonstrates some of the basic commands in Python specifically the print statement, data structures, variables, and how to define a function. This clip is from the chapter "Artificial Neural Networks" of the series...
Instructional Video6:26
Packt

Fundamentals of Neural Networks - Forward Propagation

Higher Ed
This video explains forward propagation and will dive deeper into the architecture of neural networks. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...
Instructional Video36:50
Curated Video

Fundamentals of Machine Learning - Tree-Based Methods - Part 1

Higher Ed
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...
Instructional Video9:43
Curated Video

Fundamentals of Machine Learning - Ridge

Higher Ed
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...
Instructional Video6:14
Curated Video

Fundamentals of Machine Learning - PCA

Higher Ed
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,...
Instructional Video14:32
Curated Video

Fundamentals of Machine Learning - Logistic Regression

Higher Ed
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...
Instructional Video8:43
Curated Video

Fundamentals of Machine Learning - Going Beyond Linearity

Higher Ed
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...