Below you can find my journey towards the Tensorflow Coursera Specialization Certification.
The people from DeepLearning.ai are starting a new course on Tensorflow.
The course has been renamed to:
As of this writing (18/08/2019!) It consists of four parts:
1: Introduction to TensorFlow for AI, ML and DL
2: Convolutional Neural Networks in TensorFlow
3: Natural Language Processing in TensorFlow
4: Sequences, Time Series, and Prediction
In the meantime I finished two of the four courses and I really liked it. It is very well explained by Laurence Moroney from Google and the exercises are well done. You can download all code and data to test it on you local machine. But when running the labs locally, things can get very slow (depending on your gear), the Jupyter notebooks’s are a safer bet.
There are several references to Deep Learning Specialization for people who are interested in the technical details and mathematical aspects.
13 sep 2019
I just finished the third part on NLP. This was a very practical course with lot’s of exercises. We did not go to deep into the technical details, but most of the theory on RNN, ConvNets, LSTMs can (again) be found in the Deep Learning Specialization by Prof. Ng.
28 sep 2019
I finished the final part: Sequences, Time Series and Prediction. In this part we covered the basics of predicting timeseries using classical statistical methods compared to different Neural Network methods such as RNNs and 1D ConvNets.
The four courses provide a very well structured and easy to follow introduction to Tensorflow. Most of the exercises can be done locally but some are better executed in the Google Collab environment. The lessons are short, well presented and to the point.
The only recommendation I can make is that if you are interested in Neural Networks it is better to start with this specialization and then go much deeper in the details with the Deep Learning Specialization by Prof. Ng. See my comments on this course.
I took it the other way, because at that time the Tensorflow was not available yet…
All by all, these 2 specializations are very good and you get to learn a lot.