The first lecture provides an overview of TensorFlow(TF), which is a machine learning platform of choice for many ML developers around the world. Tensorflow is developed by Google Brain team and was open sourced in Nov 2015. Since then it has been one of the most popular GitHub repo with more than 133K stars and an active community of over 2100 developers (Stats as of Aug 29, 2019).
Take a few minutes to look at this inspiring application of tensorflow in agriculture for detecting plant diseases. A lot of companies around the world are using Tensorflow to build diverse business applications around AI and ML. Check out some of the case studies about business problems solved by these corporations.
Tensorflow 2.0 is the latest release candidate (RC). TF 2.0 provies easy to use APIs for building ML models. One can train an ML model for handwritten digit recognition in less than 10 lines of code, check out this colab for such a model.
Community support and engagement:
- Contributing to TF codebase
- Ask a question on StackOverflow
- Community discussion forum
- Announcement only mailing list
Tracking TF through social media:
We will be using Google Colab for developing ML models. Please take a moment to get yourself familiarize with Colab tool. Colab can be thought of as a Jupyter notebook in cloud that needs zero configuration. It provides hardware accelerators like GPUs and TPUs and allow sharing of work with collaborators through Google drive.