Day 16: Building my own sentiment analysis program

I spent this morning creating my own sentiment analysis program using some example code. By going through the program line by line I was able to for the most part determine what was going on. After that Kushal walked me through some VQA code. VQA stands for visual question answering and it combines natural language processing (NLP) and computer vision. Using VQA you can have a model answer questions about images.  I had to load in some .json files which was slightly difficult but I managed to figure it out . These files contained over 250,000 question answers to questions based on images also found in the dataset. Tomorrow I plan to try implementing VQA code on the questions without their images to see what kind of accuracy I can achieve.

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