Doing this specialisation is probably more than the first step into Deep learning. It builds a fundamental understanding of the field. But going further, you have to practice a lot.
A person who has some basic understanding of maths, matrices and programming can benefit from this specialization and can have a good starting point to apply deep learning. On the other hand, the course can be a bit too basic for people who already have some experience in machine learning and deep learning.
Specification: Deeplearning.ai Deep Learning Specialization
|Free Trial (in days)|
|Duration (in months)|
|What will you learn?|
Artificial Neural Network, Backpropagation, Convolutional Neural Network, Deep learning, Facial Recognition System, Hyperparameter, Hyperparameter optimisation, Inductive Transfer, Long Short-Term Memory (ISTM), Machine Learning, Multi-Task Learning, Python Programming, Recurrent Neural Network, Tensorflow
|Programming Language Used|
1. Neural Networks and Deep Learning – Introduction to deep learning, Neural Networks Basics, Shallow neural networks, Deep Neural Networks.
|Graded quizzes & assignments|
7 reviews for Deeplearning.ai Deep Learning Specialization
- Taught by Andrew Ng. Andrew’s ability to clarify complicated topics in a very understandable ways is amazing. He goes deeper into the mechanics, why things work the way they work and also some of the theories behind them.
- He makes you feel motivated to learn.
- There is a YouTube version of the course, and you don’t need to pay for it, but you would only have access to the videos.
- If you are a strict hands-on learner, this specialization is probably not for you.
- It lacks the practical implementation. No end-to-end coding projects.
- Bit too basic for people who already have some experience in machine learning and deep learning.
- Data preparation is not taught.