If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.
제공자:


이 강좌에 대하여
Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.
배울 내용
Learn best practices for using TensorFlow, a popular open-source machine learning framework
Build a basic neural network in TensorFlow
Train a neural network for a computer vision application
Understand how to use convolutions to improve your neural network
귀하가 습득할 기술
- Computer Vision
- Tensorflow
- Machine Learning
Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.
제공자:

deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.
강의 계획표 - 이 강좌에서 배울 내용
A New Programming Paradigm
Welcome to this course on going from Basics to Mastery of TensorFlow. We're excited you're here! In Week 1, you'll get a soft introduction to what Machine Learning and Deep Learning are, and how they offer you a new programming paradigm, giving you a new set of tools to open previously unexplored scenarios. All you need to know is some very basic programming skills, and you'll pick the rest up as you go along. To get started, check out the first video, a conversation between Andrew and Laurence that sets the theme for what you'll study...
Introduction to Computer Vision
Welcome to week 2 of the course! In week 1 you learned all about how Machine Learning and Deep Learning is a new programming paradigm. This week you’re going to take that to the next level by beginning to solve problems of computer vision with just a few lines of code!
Enhancing Vision with Convolutional Neural Networks
Welcome to week 3! In week 2 you saw a basic Neural Network for Computer Vision. It did the job nicely, but it was a little naive in its approach. This week we’ll see how to make it better, as discussed by Laurence and Andrew here.
Using Real-world Images
Last week you saw how to improve the results from your deep neural network using convolutions. It was a good start, but the data you used was very basic. What happens when your images are larger, or if the features aren’t always in the same place? Andrew and Laurence discuss this to prepare you for what you’ll learn this week: handling complex images!
검토
- 5 stars80.49%
- 4 stars15.74%
- 3 stars2.49%
- 2 stars0.66%
- 1 star0.59%
INTRODUCTION TO TENSORFLOW FOR ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, AND DEEP LEARNING의 최상위 리뷰
Great course to get started with building Convolutional Neural Networks in Keras for building Image Classifiers. This is probably the best way to get beginners into Deep Learning for Computer Vision.
This is an introductory course on TensorFlow. The pace of the course is really good. I appreciate the pain that Prof. Andrew N G and Prof. Laurence have taken to construct and deliver this course.
Great start to learn Tensorflow .But having knowledge on theoretical and mathematical aspects is important. Instructor was good and simplified his explanations for everyone to understand better.
It's a good hands-on exercise. I like to see more link to keras api document when we introduce new function in keras. However, Tensorflow document regarding keras api is yet in complete. Thank you.
DeepLearning.AI TensorFlow 개발자 전문 자격증 정보
TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models.

자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
이 수료 과정을 구독하면 무엇을 이용할 수 있나요?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.