Machine Learning Project Using : Google Teachable Machine

Name: Machine Learning Project Using : Google Teachable Machine
Rating: 4.2 (30 reviews)

Build Machine Learning Project with Teachable Machine | Easy Machine Learning Project | Real Machine Learning Project

Created byARUNNACHALAM SHANMUGARAAJAN

Last updated 5/2025

English

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What you'll 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.

Course content

3 sections • 22 lectures • 1h 35m total length

INTRODUCTION TO TEACHABLE MACHINE1:02
Discover Google's Teachable Machine, a platform that converts a dataset into TensorFlow and Keras model for image, audio, and posts projects, with steps to train and download the model.
TEACHABLE MACHINE DASHBOARD FEATURES1:57
Explore Teachable Machine to convert datasets into TensorFlow and Keras models for image, audio, and post detection, and learn the features and options available for machine learning projects.
DATASET CREATION AND TRAINING THE MODEL5:35
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.
FACE RECOGNITION PROJECT IN PYCHARM2:12
Import the Teachable Machine model into a PyCharm machine learning project by exporting to TensorFlow Keras, using OpenCV Keras code, installing numpy in PyCharm, and running the project.
TEACHABLE MACHINE COMPLETE COURSE10:47
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.
MACHINE LEARNING PROJECT IN ROBOFLOW6:43
Learn to build a custom object detection project using Roboflow to collect, annotate, and train a YOLO v7/v8 model for ID card detection, then export datasets and deploy the model.

INTRO TO PROJECT2:02
DATASET CREATION FOR FACE RCOGNITION7:45
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.
TRAINING THE DATASET3:31
Learn to train your dataset in Teachable Machine by importing data via webcam or upload and converting it to TensorFlow and Keras models, optimizing epoch, batch size, and learning rate.
VALIDATE THE MODEL3:02
Learn how to validate your model in the teachable machine by testing face recognition with webcam, mobile phone, and image uploads, and review accuracy and precision.
DOWNLOAD THE MODEL3:04
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.
EXTRACT MODEL FILES1:56
Extract the saved Teachable Machine model, revealing two files: a Keras model file and a labels text file, with five class names prepared for a facial recognition project.
RUN AND INSTALL PACKAGAES IN PYCHARM4:58
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.
FACE RECOGNITION PROJECT OUTPUT3:56
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.

INTRO TO PROJECT2:41
Explore Teachable Machine, a Google machine learning platform, and learn how its image, audio, and pose projects enable custom object detection with TensorFlow.
DATASET CREATION7:51
Create a three-class image dataset in Teachable Machine using webcam and upload options, with Identicard, calculator, and mobile phone; capture 200 images per class with varied angles for TensorFlow training.
TRAINING THE DATASET3:28
VALIDATE THE DATASET3:53
Validate the dataset by testing the trained teachable machine with webcam and upload options, demonstrating high accuracy on identity cards, calculators, and mobile phones.
DOWNLOAD THE MODEL4:10
Learn how to download a Teachable Machine model using export options: TensorFlow.js, TensorFlow, and TensorFlow Lite, with Python keras chosen for downloading.
EXTRACT THE MODEL1:45
Learn how to extract the model and identify the extracted folder files, including Keras.h and labels.txt, for a three-class dataset in TensorFlow object detection (identity card, calculator, mobile phone).
PROJECT CODE EXPLANATION6:52
Learn to run a machine learning project in PyCharm community edition, load a Keras model and labels.txt, and use OpenCV, NumPy, and TensorFlow for webcam-based prediction.
OUTPUT AND CONCLUSION6:32
Configure python 3.9, PyCharm, and package libraries (numpy, opencv, keras) to run a custom object detection project with TensorFlow, validate via webcam, and improve accuracy with more data.

Requirements

Basic understanding of machine learning concepts.
Eagerness to explore advanced applications of machine learning with Teachable Machine.
Access to a computer with internet connectivity.

Description

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!

Who this course is for:

Developers and Programmers
Educators and Instructors
Machine learning student
Enthusiasts and Hobbyists in Machine Learning

Machine Learning Project Using : Google Teachable Machine

What you'll learn

Explore related topics

Course content

INTRODUCTION TO TEACHABLE MACHINE6 lectures • 28min

FACE RECOGNITION PROJECT IN TEACHABLE MACHINE8 lectures • 30min

OBJECT RECOGNITION PROJECT IN TEACHABLE MACHINE8 lectures • 37min

Requirements

Description

Who this course is for: