Another excellent learning materials on neural networks, decision trees, and model performance evaluation by Andrew Ng and his team. Andrew has a way of teaching difficult concepts for us to understand, especially the machine learning math intuitions.

The theory and concepts were explained really well. I however believe that if we could have video sessions for labs as well, it would have been better. Overall it was an amazing experience and I got to learn a lot of core concepts of Machine Learning

An excellent course that gives me the foundational and most important concepts on deep learning, this course shows me that the deep learning isn't a black box that only a few people understand, i can understand and i can innovate in this field also.

This course allowed you to acquire robust knowledge about neural networks, their metrics and qualitative analyses. Furthermore, it was possible to learn about other alternative learning algorithms such as decision trees, random forests and XGboost.

Another excellent class by Prof. Ng. I very much appreciate the clear explanations, careful introduction of concepts to ensure they build on each other, and even his jokes. My thanks to him and the whole team that built this series of courses.

absolutely awesome. This course and the specializatio is must to get into the mathematics of machine learning, Andrew Ng sir has a unique style of teaching and holds you right through the course. This is must to know how machine learning works.

It would be better if the notebook environment of the labs could be provided for us to download or for reference, as many of the output graphs could not shown on our jupyter notebook after we downloaded them due to missing of certain packages.

Another fantastic course by Andrew Ng and Stanford/DeepLearning.AI. Focus on neural networks and decision trees, with great practical advice for building machine learning systems in a real-world setting. Can't recommend these courses enough!

It is fascinating course! I want to thank Andrew Ng and whole team for very good explanation. Everything was clear, and especially week 3 is full of useful advices. I really enjoyed during this course. Thanks a lot. I am waiting for course 3

Great pedagogical skills. Andrew makes sure to keep the pace sustained, but each notion is clearly explained. I'm complementing my learning with some competitions on Kaggle to make sure I put into practice some of my newly acquired skills.

The content of the course is pretty good and interesting for someone with zero or basic knowledge in the field. Some basic level of programming is required but not that much. You get more from this course if you follow the specialization

What I like most about this course is that it took me step by step through equations and algorithms. It gave me deep understanding of different machine learning algorithms and the practical issues I can face when applying these tools.

This course is incredibly well-structured, have great exercises that are practical and go along the videos very well. Huge respect for Dr. Andrew Ng and all the participating members who contributed to the development of this course.

Great course! I don't see how anyone can launch into machine learning without Andrew Ng's course from Stanford University. I am grateful for the lessons and the team that put them all together! Thank you very much! God bless you!

This course has given very good insights into various supervised learning alogirithms like neural networks, optimization of neural networks, tensorflow adoption, How to address issues of overfitting / underfitting and Decision trees.

Really Helpful!!

Learned a lot about artificial Neural networks and model building. With optimizing and Activation functions and additionally learned new model like Decision Trees, Random forest and XGBoost Regressor and Classifier.

It was an excellent course to learn while completing the specialisation. But I need some statistical concepts added, such as entropy and loss difference. Please add their note for a better understanding of the different concepts.

Very good course for getting an intuition of Neural Networks. Not so helpful for practical applications of it.

The explanations are so on point it will give you great idea of working and you can by yourself master its applications

All the concepts were simply and clearly explained, and the labs ensured that I understood everything in practice. Went from zero knowledge to being able to build my own machine learning programs win a matter of weeks. Excellent.

this course gave me a good prospect toward machine learning and Neural Networks. But I believe it is not enough and exercises could be more and could be categorized in different levels so the learner could challenge themselves.

It is a great course to whom who seek the detailed information about the inside of the famous and robust algorithm like neural networks, decision tree, random forest, and XGBOOST. Thank you so much coursera, and deeplearning.ai

It's a great introduction to advanced learning algorithms, that takes the same concepts used in the first course and expands them greatly. Would be better if they added some more practice labs, but the course is great as it is

amazing course to learn the details of machine learning and deep learning and loved the way professor andrew ng taught the whole course just an amazing experience and cant wait to use the models learnt to create in daily life

Covers a range of algorithm types used in ML. I can recommend this course to anyone who's trying to break in to AI. The instructor is the best. And the content is very well structured. Thank you so much DeepLearning.ai Team

Andrew Ng is a great instructor who explains everything very clearly. The practice labs are challenging, but give hints that always ensure you can complete them. I'm really looking forward to further classes with Andrew.