This week, I worked on various different things. I started with reviewing the neural net & back propagation algorithm with Shilika. We needed to take my working implementation for one hidden layer and apply it to determine the stochastic gradient algorithm for the addition of another hidden layer. After drawing out the feed forward algorithm with the different parameters, we derived the back propagation algorithm derivatives into a simplified form and coded the equations. Shilika was in charge of the coding aspect; I simply helped her think through the algorithm.
Next, I continued working on the technical interview page. I focused on two things – improving the CSS of the page to make it more visually appealing and implementing the backend Django code for retrieving and saving the user’s answers to a database. Rather than tell the user if their answer is correct, I displayed the user’s submitted answer and the correct answer on the screen to let them decide if their answer is correct. I also created a database to store all the user information. This includes their name, email, and list of questions as well as their answers to the questions. For the CSS aspect, I played around with the layout of the page so that the chosen category and question banners appear under each other rather than next to each other. I changed the colors and positions of a few other elements to make the page, as a whole, more visually appealing. Additionally, I continued researching and adding tips to our tips page, as well as improving the CSS of that part.
Lastly, I started testing the speech recognition algorithm. I created more training data, but the addition of this training data actually decreased the accuracy of the algorithm. I haven’t found the sweet spot of the optimal number of training data samples nor the optimal parameters to run the neural network. I will experiment to find the optimal ones for next week.