Welcome to this course on TensorFlow 2.0 for Deep Learning!
In this course, you will be learning all about the TensorFlow 2.0 library open-sourced by Google. Using the library, you will also learn how to build multiple Machine Learning and Deep Learning models.
The learning objectives of the course are set out as follows:
You can expect to have all of these objectives met by the time you reach the end of this course.
If this is your first time working on Python, it may be hard for you to effectively grasp all the concepts. Therefore, the following pre-requisites are necessary for you to get the best out of the course:
If you do not have the above pre-requisites, don't worry! You can always come back later to this course once you are ready.
The course is not long but requires a good amount of attention from your end.
Before moving to the next lecture, we suggest you to set up your coding environment and open up your Jupyter Notebook. If you are a more advanced user of Python and have your own preferences, please feel free to choose an IDE that you prefer. However, all of the coding examples will be written for execution on Jupyter Notebook cells.
If you come across any problem, please check to see if your code matches exactly with the course or not. If you still are facing errors or have some doubts, please provide your question through the comment section of the specific chapter you are stuck on.
We also recommend you join our community and get connected to our vibrant network of data science aspirants. Once you are in the community, you can share your learnings, form a study group, or even get help building a project around Deep Learning using Tensorflow 2.0.
All good? Okay! Let us head on to the first lesson of the course.
Do you want to learn Python, Data Science, and Machine Learning while getting certified? Here are some best selling Datacamp courses that we recommend you enroll in: