Transfer Learning in Angular

Transfer Learning in Angular, available at $19.99, has an average rating of 2.5, with 21 lectures, based on 1 reviews, and has 3004 subscribers.

You will learn about Basics of transfer learning Applying transfer learning using TypeScript Basics of Angular apps using transfer learning Basics of image classification using machine learning This course is ideal for individuals who are JavaScript programmers interested in machine learning or Angular programmers interested in machine learning or Machine learning practitioners interested in Angular/Typescript It is particularly useful for JavaScript programmers interested in machine learning or Angular programmers interested in machine learning or Machine learning practitioners interested in Angular/Typescript.

Enroll now: Transfer Learning in Angular

Summary

Title: Transfer Learning in Angular

Price: $19.99

Average Rating: 2.5

Number of Lectures: 21

Number of Published Lectures: 21

Number of Curriculum Items: 22

Number of Published Curriculum Objects: 22

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Basics of transfer learning

Applying transfer learning using TypeScript

Basics of Angular apps using transfer learning

Basics of image classification using machine learning

Who Should Attend

JavaScript programmers interested in machine learning

Angular programmers interested in machine learning

Machine learning practitioners interested in Angular/Typescript

Target Audiences

JavaScript programmers interested in machine learning

Angular programmers interested in machine learning

Machine learning practitioners interested in Angular/Typescript

“Transfer learning deals with how systems can quickly adapt themselves to new situations, new tasks and new environments. It gives machine learning systems the ability to leverage auxiliary data and models to help solve target problems when there is only a small amount of data available in the target domain.” Transfer Learning book by Qiang Yang (Author), Yu Zhang, Wenyuan Dai, Sinno Jialin Pan

Welcome to ” Transfer Learning in Angular: learning to apply transfer learning using TensorFlow.js in TypeScript”!

In this comprehensive Udemy course, you’ll embark on a journey to master the art of transfer learning using TensorFlow.js. Transfer learning is a powerful technique that allows you to leverage pre-trained models and apply them to new tasks, saving you time and computational resources.

Throughout this course, you’ll delve into three practical approaches to transfer learning using TensorFlow.js. We’ll start by exploring Teachable Machine, an intuitive and user-friendly platform that enables you to create custom machine learning models without writing a single line of code. You’ll learn how to train your own image classifiers, and then export them as TensorFlow.js models that can be easily integrated into your web applications.

Next, we’ll dive into the K-Nearest Neighbors (KNN) algorithm as a classifier, leveraging the powerful MobileNet as a feature extractor. You’ll discover how to build robust image recognition systems by training the KNN classifier with pre-extracted features from MobileNet, enabling you to classify images with impressive accuracy. We’ll guide you through the implementation process step-by-step, ensuring you gain a solid understanding of the concepts and techniques involved.

Finally, we’ll equip you with the skills to construct a simple neural network using MobileNet as a feature extractor. You’ll learn how to fine-tune this neural network for specific tasks, such as image classification, by training it on your own custom datasets. By the end of the course, you’ll be capable of developing powerful and versatile models using TensorFlow.js, with MobileNet as your secret weapon.

What sets this course apart is the hands-on approach we adopt throughout. You’ll not only gain theoretical knowledge, but also get plenty of opportunities to put your skills into practice. We’ve designed a series of engaging exercises and coding challenges to ensure you can confidently apply what you’ve learned.

Whether you’re a beginner in machine learning or an experienced developer looking to expand your skillset, this course is tailored to suit your needs. By the end of the course, you’ll have a solid hands-on foundation in transfer learning with TensorFlow.js, enabling you to unlock the full potential of pre-trained models and build sophisticated applications that harness the power of AI.

Enroll now and embark on this exciting journey to become a TensorFlow.js transfer learning expert!

Course Curriculum

Chapter 1: Getting to know our course

Lecture 1: Initial details

Lecture 2: Seeing deep learning metaphorically

Lecture 3: Details on how transfer learning is on the course

Chapter 2: Transfer learning

Lecture 1: Initial words

Lecture 2: What is transfer learning

Lecture 3: Feature extractors for transfer learning

Lecture 4: Humans also make transfer learning

Lecture 5: Machine learning is a rule finder!

Chapter 3: Teachable Machine as a transfer learning platform

Lecture 1: Making transfer learning accessable

Chapter 4: Using mobilenet as feature extractor, and KNN as classifier

Lecture 1: Palavras iniciais

Lecture 2: Getting ready to make the feature stack for transfer learning

Lecture 3: Creating our feature model

Lecture 4: Using our features on the KNN model

Chapter 5: Using a feature model based on mobilenet for teaching a neural network

Lecture 1: Initial words

Lecture 2: Getting ready to transfer learning

Lecture 3: Precodes for training from features

Lecture 4: Getting our model to extract features from images

Lecture 5: Training our model from features from mobilenet

Lecture 6: Using our model to separate snakes from bunnies

Lecture 7: Advanced: snakes classifications

Chapter 6: Closing section

Lecture 1: Final words

Instructors

Jorge Guerra Pires
Independent Researcher, PhD

TensorFlow.js Academy
Machine learning in JavaScript

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Frequently Asked Questions

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