Machine Learning Projects Course: Teachable Machine
Machine Learning Projects Course: Teachable Machine, available at $19.99, has an average rating of 3.25, with 22 lectures, based on 21 reviews, and has 5808 subscribers.
You will learn about Explore advanced features and functionalities of Teachable Machine Extend your knowledge to multi-class classification projects Learn to apply advanced machine learning concepts to real-world scenarios. Extend your knowledge to multi-class classification projects, enabling Teachable Machine to distinguish between multiple classes or categories. This course is ideal for individuals who are Developers and Programmers or Educators and Instructors or Machine learning student or Enthusiasts and Hobbyists in Machine Learning It is particularly useful for Developers and Programmers or Educators and Instructors or Machine learning student or Enthusiasts and Hobbyists in Machine Learning.
Enroll now: Machine Learning Projects Course: Teachable Machine
Summary
Title: Machine Learning Projects Course: Teachable Machine
Price: $19.99
Average Rating: 3.25
Number of Lectures: 22
Number of Published Lectures: 22
Number of Curriculum Items: 22
Number of Published Curriculum Objects: 22
Original Price: ₹799
Quality Status: approved
Status: Live
What You Will Learn
- Explore advanced features and functionalities of Teachable Machine
- Extend your knowledge to multi-class classification projects
- Learn to apply advanced machine learning concepts to real-world scenarios.
- Extend your knowledge to multi-class classification projects, enabling Teachable Machine to distinguish between multiple classes or categories.
Who Should Attend
- Developers and Programmers
- Educators and Instructors
- Machine learning student
- Enthusiasts and Hobbyists in Machine Learning
Target Audiences
- Developers and Programmers
- Educators and Instructors
- Machine learning student
- Enthusiasts and Hobbyists in Machine Learning
Course Title: Learn Machine Learning Project Course : Teachable Machine
Course Description:
Welcome to the Learn Machine Learning Advanced Course: Teachable Machine, an immersive journey into the advanced realms of machine learning using Google’s powerful Teachable Machine platform. Whether you’re a seasoned developer, educator, or an enthusiastic learner, this course is meticulously crafted to expand your proficiency in machine learning and empower you to create sophisticated and interactive applications.
What You Will Learn:
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Advanced Teachable Machine Mastery:
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Explore advanced features and functionalities of Teachable Machine, gaining a comprehensive understanding of its capabilities.
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Custom Models with Transfer Learning:
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Dive into the world of transfer learning, mastering techniques to create custom machine learning models tailored to specific applications.
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Fine-Tuning and Optimization Techniques:
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Learn the art of fine-tuning machine learning models, optimizing them for enhanced performance and accuracy in diverse scenarios.
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Multi-Class Classification Projects:
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Extend your machine learning skills to tackle multi-class classification projects, allowing Teachable Machine to distinguish between multiple classes or categories seamlessly.
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Object Detection and Image Segmentation:
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Delve into advanced computer vision applications, exploring object detection and image segmentation with Teachable Machine for sophisticated visual recognition.
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Speech and Sound Recognition:
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Unlock the potential of Teachable Machine in recognizing and classifying speech and sounds, expanding your capabilities in audio-based machine learning.
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Real-Time Integration with External Platforms:
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Master the art of real-time integration, seamlessly connecting your Teachable Machine models with external platforms and applications for practical deployment.
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Interactive Applications with Gesture Recognition:
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Elevate your projects by incorporating gesture recognition, enabling you to create interactive applications that respond intelligently to user movements.
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Ethical Considerations in Machine Learning:
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Engage in meaningful discussions on the ethical considerations inherent in machine learning applications, emphasizing responsible and inclusive development practices.
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Who Is This Course For:
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Developers and Programmers seeking advanced machine learning skills.
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Educators and Instructors incorporating Teachable Machine into their teaching.
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Creative Professionals and Designers interested in innovative applications.
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Enthusiasts and Hobbyists passionate about exploring the cutting-edge of machine learning.
Requirements:
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Basic understanding of machine learning concepts.
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Access to a computer with internet connectivity.
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Eagerness to explore advanced applications of machine learning with Teachable Machine.
Why Enroll:
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Hands-On Learning: Engage in practical projects for each advanced concept covered in the course.
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Real-World Applications: Learn to apply advanced machine learning concepts to real-world scenarios.
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Community Support: Join a community of learners, share experiences, and get assistance from instructors and peers.
Embark on this advanced machine learning journey with Teachable Machine and emerge as a proficient practitioner in the dynamic field of artificial intelligence. Enroll now and take the next step in mastering advanced machine learning applications!
Course Curriculum
Chapter 1: INTRODUCTION TO TEACHABLE MACHINE
Lecture 1: INTRODUCTION TO TEACHABLE MACHINE
Lecture 2: TEACHABLE MACHINE DASHBOARD FEATURES
Lecture 3: DATASET CREATION AND TRAINING THE MODEL
Lecture 4: FACE RECOGNITION PROJECT IN PYCHARM
Lecture 5: TEACHABLE MACHINE COMPLETE COURSE
Lecture 6: MACHINE LEARNING PROJECT IN ROBOFLOW
Chapter 2: FACE RECOGNITION PROJECT IN TEACHABLE MACHINE
Lecture 1: INTRO TO PROJECT
Lecture 2: DATASET CREATION FOR FACE RCOGNITION
Lecture 3: TRAINING THE DATASET
Lecture 4: VALIDATE THE MODEL
Lecture 5: DOWNLOAD THE MODEL
Lecture 6: EXTRACT MODEL FILES
Lecture 7: RUN AND INSTALL PACKAGAES IN PYCHARM
Lecture 8: FACE RECOGNITION PROJECT OUTPUT
Chapter 3: OBJECT RECOGNITION PROJECT IN TEACHABLE MACHINE
Lecture 1: INTRO TO PROJECT
Lecture 2: DATASET CREATION
Lecture 3: TRAINING THE DATASET
Lecture 4: VALIDATE THE DATASET
Lecture 5: DOWNLOAD THE MODEL
Lecture 6: EXTRACT THE MODEL
Lecture 7: PROJECT CODE EXPLANATION
Lecture 8: OUTPUT AND CONCLUSION
Instructors
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ARUNNACHALAM SHANMUGARAAJAN
Computer Science Student
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 2 votes
- 3 stars: 4 votes
- 4 stars: 3 votes
- 5 stars: 10 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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