
Create a two-class face dataset with webcam and uploaded images, train a TensorFlow and Keras model in Teachable Machine, and export the model for Python or JavaScript projects.
Explore Teachable Machine’s three project types—image, audio, and post—and learn to convert datasets into TensorFlow and Keras models, train them, and export for Python or web projects.
Learn to create a face recognition dataset in Teachable Machine by building five classes, collecting at least 500 images per class with varied angles, and importing via webcam or upload.
Learn to export and download Teachable Machine models using TensorFlow.js, TensorFlow, or TensorFlow Lite. Choose TensorFlow and Keras to download the model, and understand JavaScript and Python workflow options.
Install numpy, OpenCV contrib Python, and Keras in PyCharm. Copy Teachable Machine code into the project and run the facial recognition model using the extracted Keras.h5 and labels.txt.
Execute the facial recognition project with Teachable Machine in PyCharm, training and validating the dataset via webcam. Download the model and assess accuracy and precision in the TensorFlow workflow.
Build Machine Learning Project with Teachable Machine | Easy Machine Learning Project | Real Machine Learning Project
Course Description:
Welcome to "Machine Learning Project Using: Teachable Machine", a beginner-friendly and practical course designed to introduce you to the exciting world of machine learning without requiring extensive programming knowledge! In this course, you’ll learn to create, train, and deploy machine learning models quickly and effectively using Google’s Teachable Machine platform.
Teachable Machine is a user-friendly web-based tool that simplifies machine learning, making it accessible to everyone, from students and educators to developers and hobbyists. With this platform, you can build AI models for image, sound, and pose recognition in just a few steps!
If you're looking for a Machine Learning Project that’s beginner-friendly and doesn’t require deep coding knowledge, you’ve come to the right place. This course will guide you step-by-step in building a practical and powerful Machine Learning Project using the Teachable Machine platform.
With a focus on real-world applications, you’ll create a Machine Learning Project involving image classification, sound recognition, and pose detection. Teachable Machine allows you to train models quickly and visually, and we’ll explore how to integrate your Machine Learning Project into websites and apps.
Whether you’re a student, teacher, developer, or hobbyist, this course will help you start your journey into Machine Learning Projects in the most simple yet powerful way.
Why Take This Course?
It’s a beginner-friendly approach to Machine Learning Projects
No prior ML or coding experience needed
Visual and interactive training with real use-cases
Export and deploy your Machine Learning Project easily
What You’ll Learn:
Introduction to Machine Learning: Understand the basics of machine learning and how Teachable Machine simplifies the process.
Setting Up Teachable Machine: Learn how to access and navigate the platform.
Data Collection and Training: Create custom datasets by uploading images, sounds, or pose examples and train your model efficiently.
Model Testing and Evaluation: Test your trained model’s performance and refine it for improved accuracy.
Exporting and Deployment: Deploy your machine learning models in various applications such as websites, apps, or standalone systems.
Real-World Applications: Explore diverse use cases like gesture-controlled apps, sound recognition systems, and image classification projects.
By the end of this course, you’ll have a complete understanding of how to use Teachable Machine to create innovative machine learning projects. You’ll also walk away with your very own project, ready to showcase to peers, employers, or clients!
Join us today and start your machine learning journey with Teachable Machine!