Many times, developers have been left scratching their heads figuring out the best way to pass in variables at different stages of development and deployment. I, myself, are guilty of that. To solve this once and for all, I decided to experiment and note down my observations in this article. 🤗

When I first stepped into the field of machine learning, I spent quite a large amount of time on reading papers and trying to implement them. Of course, I was no genius and by implementing I meant git clone and trying to run the authors’ code. For concepts that interests me, I’d also type out the code and annotate them to get a better understanding. I imagine many others to have the similar journey when starting out.

Word2Vec is touted as one of the biggest, most recent breakthrough in the field of Natural Language Processing (NLP). The concept is simple, elegant and (relatively) easy to grasp. A quick Google search returns multiple results on how to use them with standard libraries such as Gensim and TensorFlow. Also, for the curious minds, check out the original implementation using C by Tomas Mikolov. The original paper can be found here too.

In this article, I will summarize the important concepts from each chapter of this book and bring out the crux of what you need to know in 15 minutes. There are also additional links to keywords to help you research further.