online gambling singapore online gambling singapore online slot malaysia online slot malaysia mega888 malaysia slot gacor live casino malaysia online betting malaysia mega888 mega888 mega888 mega888 mega888 mega888 mega888 mega888 mega888 Top 16 Best Online Deep Learning Courses to learn in 2022


images/2022-02-20_211900.png

▲圖片標題(來源:CIO Taiwan)

What is Deep learning?

The field of artificial intelligence is essentially when machines can do tasks that typically require human intelligence. It encompasses machine learning, where machines can learn by experience and acquire skills without human involvement. Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. Similarly to how we learn from experience, the deep learning algorithm would perform a task repeatedly, each time tweaking it a little to improve the outcome. We refer to ‘deep learning’ because the neural networks have various (deep) layers that enable learning. Just about any problem that requires “thought” to figure out is a problem deep learning can learn to solve.

Hera re the some of the best deep learning courses you must learn in 2022 to boost your career in AI.

1. Deep Learning Nano degree (Udacity)

Who can take this course: This deep learning certification is best for students who have a basic working knowledge of Python programming. However, the course starts off with relatively simple lessons, so it’s certainly possible to learn programming hand-in-hand with this course. Prior knowledge in deep learning is not required.

2. Deep Learning Specialization (Coursera)

Who can learn this course: This deep learning certification program from Coursera is ideal for students who know basic Python programming and algebra. Prior knowledge in deep learning is considered beneficial, but not compulsory.

3. Complete Guide to TensorFlow for Deep Learning with Python (Udemy)

Who can take this course: Anyone who wants to dive into Google’s TensorFlow system stands to benefit the most from this course. The course content is introductory in nature, so prior knowledge in programming is not compulsory (although it will be beneficial).

4. Deep Learning A-Z: Hands-On Artificial Neural Networks (Udemy)

Who can learn this course: Students interested in getting into the thick of coding their own deep learning algorithms should take this course. Alternatively, those looking for a program that teaches deep learning training with PyTorch and TensorFlow will find lots to learn from this course. The material is relatively basic in nature, so this course could be considered beginner-friendly.

5. TensorFlow 101: Introduction to Deep Learning (Udemy)

Ready to build the future with Deep Neural Networks? Stand on the shoulder of TensorFlow and Keras for Machine Learning.

6. Deep Learning, by 3Blue1Brown (YouTube)

Who can learn this course: This deep learning course is unlike all others on this list. It’s very easy to follow, it does not require any prerequisite knowledge, and it’s suitable for absolutely anyone interested in deep learning and neural networks.

7. Deep Learning: Recurrent Neural Networks in Python (Udemy)

Who can take this course: Data engineers looking to gain some experience with deep learning are the ideal candidates for this course. The course requires you to have prior knowledge of the basics of deep learning algorithms alongside experience with Hidden Markov models.

8. Deep Learning with Keras (Pluralsight)

Who can learn this course: This deep learning course is basic in nature, but it’s still best suited for students who have some prior skills in programming (mainly Python).

9. Introduction to Deep Learning (Coursera)

What you’ll learn: This course teaches students about the basics of neural networks, the kinds of data that you can expect to use them on, and the applications you can create that use these processes. Learn about how your algorithms can generate content from context and generate actionable data from raw input. It also gives a succinct explanation of the role of deep learning in different directions of AI, and shows basic examples of each.

10. Full Stack Deep learning course

There are many great courses to learn how to train deep neural networks. However, training the model is just one part of shipping a deep learning project. This course teaches full-stack production deep learning:

11. Deep learning crash Course (Youtube Learning)

Instead of providing them with a comprehensive set of rules, we could show them some examples so that they can understand how the world works. That’s what machine learning does.

12. Practical Deep Learning for Coders by fast.ai

This is Jeremy Howard’s classic course on deep learning. He is another awesome instructor in the field of Deep Learning along with Andrew Ng of Coursera and Kirill Eremenko on Udemy.

轉貼自: BDAN


留下你的回應

以訪客張貼回應

0
  • 找不到回應

YOU MAY BE INTERESTED