Enroll Course: https://www.coursera.org/learn/getting-started-with-tensor-flow2
If you’re looking to dive into the world of deep learning, the “Getting Started with TensorFlow 2” course on Coursera provides you with a comprehensive foundation to do just that. This course has been crafted to guide you through the foundational concepts of TensorFlow 2, taking you from a beginner level to a proficient user capable of developing deep learning models.
### Overview
In this course, you will learn about the complete end-to-end workflow for developing deep learning models using TensorFlow, one of the most widely-used libraries in the field. The course introduces you to various essential components of deep learning model development including building, training, and evaluating models, while also delving into best practices like model validation, regularization, and callbacks.
### Course Syllabus Breakdown
– **Introduction to TensorFlow**: The journey begins with an introduction to TensorFlow, its installation, and the tools available such as Google Colab which eases coding. This week sets the tone for a successful learning experience.
– **The Sequential Model API**: Here, you will get hands-on experience with the Keras API—a user-friendly interface for building models quickly. By undertaking a programming assignment, you will develop an image classification model from the MNIST dataset, an essential exercise that solidifies your understanding by applying theoretical knowledge.
– **Validation, Regularisation, and Callbacks**: Understanding how to validate your models is pivotal in deep learning. In this week, you will learn to use a validation dataset and incorporate regularisation techniques to enhance model performance. The assignment focuses on applying these concepts to the well-known Iris dataset.
– **Saving and Loading Models**: This week delves into the practical aspects of saving and loading your models, ensuring that your hard work can be preserved and reused. You will explore different methods for saving, including saving only the model weights, and will engage in an assignment focusing on a model trained with satellite images.
– **Capstone Project**: To wrap up your learning experience, the course culminates in a capstone project where you apply all the knowledge you have garnered throughout the program to develop your very own deep learning classifier on a labeled dataset of street view house numbers. This project serves as the perfect opportunity to demonstrate your skills and understanding of the concepts learned.
### Final Thoughts
“Getting Started with TensorFlow 2” is an excellent starting point for anyone interested in deep learning. It combines theoretical knowledge with practical exercises that reinforce learning and encourage mastery of content. The structure and delivery of the course make it suitable for both beginners and those looking to streamline their learning process in deep learning.
### Recommendation
I highly recommend this course, especially if you’re a newcomer to deep learning or seeking to upgrade your skills with TensorFlow. The hands-on approach and the structured flow ensure that you build confidence as you progress. Whether you’re a student, a professional looking to pivot your career, or just a tech enthusiast, this course is sure to equip you with the skills necessary to excel in the domain of artificial intelligence.
Enroll Course: https://www.coursera.org/learn/getting-started-with-tensor-flow2