Have you completed studying this resource?: I mean I compiled it so yea 😛
Your review of this resource: Gives an in depth epxlanation of execution of the code which are required in the course
Why do you think this resource will be useful for others?: From a cld perspective, I felt that the jump NLP1 made from cl2 to nlp1 was huge, and majority of the time I had to spend was on coding and understanding of how to code stuff up. Hence the repo I have linked have code with algorithms explained with execution.
Statistical: Explains properly the alogirthms used for Kneyser Ney and Witten Bell smoothing, and their execution
Neural: Explains in depth of all the decisions which I took to create a basic Language Model. This also explains dimensions properly, which I felt was the toughest part to understand with respect to NNs.
Resource Name: Intro-to-NLP1
Contributor (your) Name: Shivansh S
Resource Links: https://github.com/AurumnPegasus/Intro-to-NLP1
Have you completed studying this resource?: I mean I compiled it so yea 😛
Your review of this resource: Gives an in depth epxlanation of execution of the code which are required in the course
Why do you think this resource will be useful for others?: From a cld perspective, I felt that the jump NLP1 made from cl2 to nlp1 was huge, and majority of the time I had to spend was on coding and understanding of how to code stuff up. Hence the repo I have linked have code with algorithms explained with execution.