Celebrate that I have passed another busy week, and have finished three midterm exams! In order to improve the communication between team members, we added a meeting on Monday evening. Originally, our purpose was to complete the collaboration of the individual assignment last week. However, we realized that there was no assignment for collaboration this week, so we switched to exchanging information about the project and correct definitions of some terms given in HP’s official documents. At the same time, I started to improve my development environment, such as configuring the Flask and React running environment.
In the middle of this week, I discussed the design tool selection and learning curve with people in the discussion group. Two (to be precise, one, because I already have the experience of using LucidChart) design tools were added to my learning plan and prepared to use them in the design part of the project. I started to use LucidChart as my default UML diagram creating tool after the recommendation of my previous group mates. It is indeed very intuitive to provide users with all the functions needed to create UML diagrams.
I am also learning to use TensorBoard. My project may also involve the use of TensorFlow for NN development in the later stage. TensorBoard is the official visualization tool of Tensorflow, which can be used to display TensorFlow images, draw the quantitative index graphs generated by the images and additional data. When using Tensorflow to train a large number of deep neural networks, we hope to track the information of the entire training process of the neural network, such as how the parameters of each layer change and distribute during the iteration process, such as the model after each cycle parameter update What is the accuracy of the test set and training set, such as the change of loss value, etc. And TensorBoard can record and visualize some information during the training process.
Later, at the meeting on Friday, HP provided us with the code of a part of the project that they have completed. After browsing and running these codes, I have a deeper understanding of the project partner’s performance of the final result of this project.
