Introduction to TensorFlow for Artificial Intelligence Machine Learning and Deep Learning

2.4
2.4 rating

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.

The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work we recommend that you take the Deep Learning Specialization.

WEEK 1
6 hours to complete
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.
SHOW ALL SYLLABUS
SHOW ALL
4 videos (Total 16 min) 5 readings 3 quizzes

WEEK 2
7 hours to complete
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!
Check out this conversation between Laurence and Andrew where they discuss it and introduce you to Computer Vision!
7 videos (Total 15 min) 6 readings 3 quizzes

WEEK 3
8 hours to complete
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.
6 videos (Total 19 min) 6 readings 3 quizzes

WEEK 4
9 hours to complete
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!
9 videos (Total 27 min) 10 readings 3 quizzes


Tham gia đánh giá khóa học

Nếu bạn đã học qua khóa học này thì mời bạn tham gia đóng góp ý kiến và đánh giá để cộng đồng bạn học có thêm thông tin tham khảo.

Cung cấp bởi: Coursera /  deeplearning.ai

Thời lượng: 30 giờ
Ngôn ngữ giảng dạy: Tiếng Anh
Chi phí: Miễn phí / 0
Đối tượng: Intermediate

Thông tin về nhà cung cấp

Coursera (/ kərˈsɛrə /) là một nền tảng học tập trực tuyến toàn cầu được thành lập vào năm 2012 bởi 2 giáo sư khoa học máy tính của đại học Stanford là Andrew NgDaphne Koller, nền tảng này cung cấp các khóa học trực tuyến (MOOC) cho cộng đồng người học online.

Coursera hợp tác với các trường đại học danh tiếng tại Bắc Mỹ và trên khắp thế giới, cùng với nhiều tổ chức khác để cung cấp các khóa học trực tuyến chất lượng, theo chuyên ngành và được cấp chứng chỉ trong nhiều lĩnh vực như kỹ thuật, khoa học dữ liệu, học máy, toán học, kinh doanh, khoa học máy tính, tiếp thị kỹ thuật số, nhân văn, y học, sinh học, khoa học xã hội , và nhiều ngành khác.

Các khóa học cùng chủ đề

Visual Perception for Self-Driving Cars

This course will introduce you to the main perception tasks in autonomous driving, static and dynamic object detection, and will survey common computer vision methods for robotic perception. By the...

Motion Planning for Self-Driving Cars

This course will introduce you to the main planning tasks in autonomous driving, including mission planning, behavior planning and local planning. By the end of this course, you will be...

Capstone: Autonomous Runway Detection for IoT

This capstone project course ties together the knowledge from three previous courses in IoT though embedded systems: Development of Real-Time Systems Web Connectivity & Security and Embedded Hardware and Operating...

Leave a Reply

Your email address will not be published. Required fields are marked *

Scroll to Top