In this blogpost, I will be addressing the question I get all the time from colleagues and researchers:
” How to get started with Deep Learning? “
As with learning any new concept in the computing field, the following two main sections are involved in the process of learning the new concept:
- Theoretical understanding of the topic
- Hands-on and practical implementation
Therefore, I decided rather than writing the concepts here, I will cite the best resources that helped me personally take off in this area.
So let us get started!
In terms of books, there are many good books out there that focuses on the mathematical details behind Deep Learning, however, I found that there were two books in particular that were easy to read and cover so much details. Hence, reading them will help you to build a strong foundation without digging too much into the maths:
- Deep Learning with Python by François Chollet
- Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Tensorflow tutorials are the best for hands-on experience with different deep learning models and architectures, I highly recommend that you try to run some of their code and observe the results.
Moving on to online courses:
- Coursera’s Deep Learning course is very helpful and interesting.
When it comes to youtube channels, here are my recommendations:
For more recommendations on other helpful resources Python Programmer youtube channel offers a great range is a great of material that varies in difficulty.
Finally, I would recommend reading many many research papers in deep learning and its applications. Not only they show how fascinating and powerful deep learning is, but they provide an in-depth explanation on different implementation techniques.
By completing all the above, you should be good to go.
Please let me know if you found these resources helpful and feel free to add any other recommendations in the comment section below.
Wish you a great day!
PS. I am not sponsored these authors or organisations. However, the links of the books mentioned above are affiliated.