Introduction to Image Classification with Python: A Beginner
Requirements
- Basic knowledge of Python programming is recommended
Description
Welcome to "Introduction to Image Classification with Python: A Beginner's Guide"! This course is designed to provide you with a comprehensive understanding of image classification, an essential task in the field of machine learning and artificial intelligence. Whether you're a student, a hobbyist, or a professional looking to dive into the world of image processing, this course is perfect for you.
Throughout this course, you'll learn the fundamentals of image classification, starting with setting up your Python environment using Google Colab. You'll get hands-on experience installing and configuring Python, creating a virtual environment, and installing essential libraries like NumPy, Pandas, Matplotlib, OpenCV, and TensorFlow/Keras.
We will explore the CIFAR-10 dataset, teaching you how to load, visualize, and understand the data. You'll learn important preprocessing techniques such as normalization, one-hot encoding, and splitting data into training and validation sets. Building on this foundation, you'll dive into the world of Convolutional Neural Networks (CNNs), understanding their architecture and building your first CNN model using Keras.
Training and evaluating your model will be covered in depth, along with fine-tuning and optimizing your model for better performance. You'll also learn how to handle imbalanced data using various techniques to ensure your model is fair and accurate.
Finally, we'll guide you through saving, loading, and deploying your trained models, giving you practical experience in taking your models from development to production.
By the end of this course, you'll have a solid foundation in image classification and the skills needed to tackle more advanced projects. Join us and start your journey into the exciting world of image classification with Python!
Who this course is for:
- This course is designed for absolute beginners who are interested in learning about image classification using Python. It's ideal for students, hobbyists, and professionals who want to gain foundational skills in deep learning.
Instructor
- 4.5 Instructor Rating
- 321 Reviews
- 6,539 Students
- 3 Courses
My name is Meenakshi Nair, a high school senior from the San Francisco Bay Area, the world’s hub of technological development.
I was interested in technology from a very young age. I learned Python and java in middle school and started building mobile applications using Thunkable and Swift since 7th grade.
The COVID-19 pandemic changed my thought process and perception of technology. I became more interested in real-world applications and the impacts of technology on people during the lock down.This new perspective led me to build a CO2 tracking and monitoring tool using Arduino and Python along with a group of two friends.
The app aimed to help businesses safely reopen and recover from COVID impacts. The app was built for IOS using Apple’s native IOS development environment, the Swift language, Google Cloud for Data Storage, HighCharts for trend analysis, and Text Recognition AIs provided by Apple’s CoreML.
My team was invited to pitch our app at Technovation’s annual World Summit event as a finalist team selected from over 2,700 teams from 62 countries and won the Technovation Girls Junior Division Grand Prize. I have been a Technovation ambassador for last four years, where my role is to make sure that girls in my community are aware of the program and support them through the Technovation journey.
I am also passionate about conducting research and working on projects involving engineering, computer science and AI. I have published research papers on AI/ ML applications to solve real world challenges. My research has won special awards at International Science and Engineering Fair (ISEF 2024). In my free time, I enjoy photography, dance, and taekwondo.