In this video, we will get introduced to the concept of transfer learning.
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This clip is from the chapter "Transfer Learning for Computer Vision" of the series "Deep Learning - Convolutional Neural Networks with TensorFlow".In...

In this video, we will discuss the two approaches used for transfer learning, which we will use in the next videos.
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This clip is from the chapter "Transfer Learning for Computer Vision" of the series "Deep Learning -...

This video covers best practices for building and deploying ML models in Alteryx, providing examples of how machine learning can be used to solve specific business problems, customer segmentation, fraud detection, and churn...

If I had to learn machine learning from scratch, here’s how I’d do it.

This video explains the various classification models in machine learning.
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This clip is from the chapter "Appendix - Machine Learning Topics for the Legacy AWS Certified Big Data Exam" of the series "AWS Certified Data...

Training a classification model to predict the class of an Iris flower.

From the section: Simple Classification Tree. This section we will expand our knowledge of regression Decision tree to classification trees, we will also learn how to create a classification tree in Python.



Simple...

This case study is to determine the factors (inputs) that have correlation to the concrete compressive strength (output).



0:00 In
troduction
2:35 Download J
upyter Notebook
4:00 Import Machine Learni
ng Packages...

Explains the difference between binary and multiclass classification problem.

From the section: Machine Learning: Part 1. In this section, we’ll learn how machine learning works, and how it fits in with the world of AI and deep learning. And learn to train, test and validate the data using K-fold...

From the section: Machine Learning: Part 1. In this section, we’ll learn how machine learning works, and how it fits in with the world of AI and deep learning. And learn to train, test and validate the data using K-fold...

This video explains linear regression in R.
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This clip is from the chapter "Linear Regression - a Real Model" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for 2021]".This section explains...

Logistic regression is a machine learning algorithm for classification. In this algorithm, the probabilities describing the possible outcomes of a single trial are modeled using a logistic function. Logistic regression...

Classification predicts discrete labels (outcomes) such as yes/no, True/False, or any number of discrete levels such as a letter from text recognition, or a word from speech recognition. There are two main methods for...

26 - ML Draw Classification

From the section: Machine Learning: Part 1. In this section, we’ll learn how machine learning works, and how it fits in with the world of AI and deep learning. And learn to train, test and validate the data using K-fold...

This video introduces you to logistic regression.
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This clip is from the chapter "Logistic Regression" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for 2021]".This section explains...

This video explains logistic regression in R.
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This clip is from the chapter "Logistic Regression" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for 2021]".This section explains logistic...

Training and testing are often performed once on a dedicated computing platform. The trained model is then packaged for another computing system for predictions.



Deploying machine learning is the process of making the...

From the section: Machine Learning: Part 2. In this section, we’ll cover Bayes Theorem, Naive Bayes, SVM and SVC to classify data.<b<br/>r/>

Machine Learning: Part 2: [Activity] Support Vector Classifiers in Action

From the section: Machine Learning: Part 2. In this section, we’ll cover Bayes Theorem, Naive Bayes, SVM and SVC to classify data.<b<br/>r/>

Machine Learning: Part 2: [Activity] Naive Bayes in Action

Imbalanced data is a disproportionate number of data points with discrete labels and can be a big challenge to develop an accurate classifier. A classifier attempts to find the data boundary where one class ends and the other begins....

From the section: Deep Learning and Tensorflow: Part 1. In this section, we’ll talk about what Deep Learning is, and how TensorFlow works at a low level.



Deep Learning and Tensorflow: Part 1: Building Deep Neural Networks...

In this video, we will cover applications of machine learning.
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This clip is from the chapter "Introduction to Machine Learning" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we...