Transfer Learning in Angular

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Jorge Guerra Pires,TensorFlow.js Academy

2:21:50

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1. Getting to know our course

1.1 GitHub repository.html

1. Initial details.mp4

06:25

2. Seeing deep learning metaphorically.mp4

05:30

3. Details on how transfer learning is on the course.mp4

02:55

2. Transfer learning

1.1 transfer learning.pptx

1. Initial words.mp4

03:14

2. What is transfer learning.mp4

03:01

3. Feature extractors for transfer learning.mp4

04:49

4. Humans also make transfer learning.mp4

03:45

5. Machine learning is a rule finder!.mp4

02:57

3. Teachable Machine as a transfer learning platform

1. Making transfer learning accessable.mp4

17:49

4. Using mobilenet as feature extractor, and KNN as classifier

1. Palavras iniciais.mp4

05:54

2. Getting ready to make the feature stack for transfer learning.mp4

06:23

3. Creating our feature model.mp4

08:29

4. Solving a problem mobilenet does not work.html

5. Using our features on the KNN model.mp4

06:26

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

1. Initial words.mp4

05:00

2. Getting ready to transfer learning.mp4

10:34

3. Precodes for training from features.mp4

10:12

4. Getting our model to extract features from images.mp4

09:20

5. Training our model from features from mobilenet.mp4

09:28

6. Using our model to separate snakes from bunnies.mp4

09:39

7. Advanced snakes classifications.mp4

06:58

6. Closing section

1. Final words.mp4

03:02

Description

learning to apply transfer learning using TensorFlow.js in TypeScript

What You'll 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 is this for?

JavaScript programmers interested in machine learning

Angular programmers interested in machine learning

Machine learning practitioners interested in Angular/Typescript

What You Need to Know?

Tried to explain all, but basics of TensorFlowjs and Angular may be advantageous

More details

Description
"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!

Who this course is for:
JavaScript programmers interested in machine learning
Angular programmers interested in machine learning
Machine learning practitioners interested in Angular/Typescript

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Angular

Jorge Guerra Pires

Instructor's Courses

I have been working with computer programming and mathematical modeling applied to biological systems since my bachelor of Engineering.Currently, I am an Independent Researcher and Member of the Center of Excellence for Research DEWS (University of L'Aquila, DISIM, Italy)Short-bio (EN): B.Eng by Universidade Federal de Ouro Preto (Brazil) in Production Engineering; double master degree by University of L'Aquila and Gdansk University of Technology: PhD on a collaboration between the Brazilian programme Science without Borders in biomathematics at the University of L'Aquila/IASI-CNR/BioMathLab. Master of science and PhD degrees recognized in Brazil by University of São Paulo (USP) as bioinformatics. Postdoc by Federal University of Bahia and Fiocruz.Academia Edu140 Followers | 12 Following | 5 Co-authors | 8,654Total Views | top 2%.Biografia curta: Tenho trabalhado com programação de computadores e modelagem computacional aplicado a sistemas biológicos.Alguns detalhas da minha formação:•Sou formado pela UFOP em engenharia de produção;•Tenho mestrado pela Universidade de L’Aquila e Técnica de Gdansk;•Tenho doutorado pela Universidade de L’Aquila;•Tenho um postdoc pela UFBA e terminei um outro pela Fiocruz;•Meus diplomas no exterior foram reconhecidos pela USP em bioinformática;

TensorFlow.js Academy

Instructor's Courses

TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js.On this profile, we explore the interception mainly with TypeScript/Angular. However, when the case, we may explore also in pure JavaScript. Our focus are applications, Practical TensorFlow.js, we like to get our hands pretty duty making awesome apps!

Udemy

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