Word2Vec prediction

For a data science interview I’m currently working on a case study for using Word2Vec encoded words with a resulting dimension of 256 on roughly 1100 samples in total. I got a pre labeled dataset for which in want to build the best performing ML/ DL model, I already tried Xgboost and some simple models such as MLP and some very basic CNNs. But I feel like my data size is not rly large enough to really try with anything …

build case case study data data science dataset deeplearning interview mlp prediction samples science simple study total word2vec words xgboost